Publications:
journal papers / conference papers
[64] Investigation to answer three key questions concerning plant pest identification and development of a practical identification framework, Quan Huu Cap, Atsushi Fukuda, and Hitoshi Iyatomi, Biomedical Signal Processing and Control, 2024. (accepted) arXiv preprint arXiv:2304.01864
[63] A Practical Framework for Unsupervised Structure Preservation Medical Image Enhancement, Ryosuke Wayama, Yuki Sasaki, Satoshi Kagiwada, Nobusuke Iwasaki, and Hitoshi Iyatomi, Computers and Electronics in Agriculture, Vol. 222, 109021, 2024.
[62] Normalizing Flow to Augmented Posterior: Conditional Density Estimation with Interpretable Dimension Reduction for High Dimensional Data, Cheng Zeng, George Michailidis, Hitoshi Iyatomi and Leo L Duan, International Journal of Computer and Information Engineering, vol. 18, no. 5, pp. 306-315, 2024. Link
[61] Towards Robust Plant Disease Diagnosis with Hard-sample Re-mining Strategy, Quan Huu Cap, Atsushi Fukuda, Satoshi Kagiwada, Hiroyuki Uga, Nobusuke Iwasaki, and Hitoshi Iyatomi, Computers and Electronics in Agriculture, Vol. 215, 108375, 2023. paper with code / Link
[60] PCSS: Skull Stripping with Posture Correction from 3D Brain MRI for Diverse Imaging Environment, Ken Nishimaki, Kumpei Ikuta, Shingo Fujiyama, Kenichi Oishi and Hitoshi Iyatomi, IEEE Access, vol. 11, pp. 116903-116918, 2023. Link
[59] Image analysis in advanced skin imaging technology, Lei Bi, M Emre Celebi, Hitoshi Iyatomi, Pablo Fernandez-Penas, Jinman Kim, Computer Methods and Programs in Biomedicine, vol. 238, p.107599, 2023. (Editorial) Link
[58] (In Japanese) ネガティブニュースがユーザー行動に与える影響の調査, 大畑和也，飯塚洸二郎，彌冨 仁、Data-Driven Studies, vol. 1, article 7, 2023. Link
[57] DM2S2: Deep Multimodal Sequence Sets with Hierarchical Modality Attention, Shunsuke Kitada, Yuki Iwasaki, Riku Togashi, and Hitoshi Iyatomi, IEEE Access, vol.10, pp. 120023-120034, 2022. Link
[56] Making Attention Mechanism More Robust and Interpretable with Virtual Adversarial Training, Shunsuke Kitada, and Hitoshi Iyatomi, Applied Intelligence, 2023. (accepted)
[55] (In Japanese) 実践的な植物病自動診断のための画像生成技術, 彌冨 仁、粉体工学会誌, Vol. 59, No. 3, pp.394-399, 2022. Link / PDF (3.56MB)
[54] Ad Creative Discontinuation Prediction with Multi-modal Multi-task Neural Survival Networks, Shunsuke Kitada, Hitoshi Iyatomi and Yoshifumi Seki, Applied Sciences, vol. 12, no.7, 3594, 2022. https://doi.org/10.3390/app12073594 / Link
[53] Disease-oriented image embedding with pseudo-scanner standardization for content-based image retrieval on 3D brain MRI, Hayato Arai, Yuto Onga, Kumpei Ikuta, Yusuke Chayama, Hitoshi Iyatomi and Kenichi Oishi, IEEE Access, vol. 9, pp. 165326-165340, doi: 10.1109/ACCESS.2021.3129105, 2021. Link
[52] Attention Meets Perturbations: Robust and Interpretable Attention with Adversarial Training, Shunsuke Kitada and Hitoshi Iyatomi, IEEE Access, vol. 9, pp. 92974-92985, 2021. Link
[51] LASSR: Effective Super-Resolution Method for Plant Disease Diagnosis, Quan Huu Cap, Hiroki Tani, , Satoshi Kagiwada, Hiroyuki Uga and Hitoshi Iyatomi, Computers and Electronics in Agriculture, 187, 106271, 2021. arXiv preprint arXiv:2010.06499 / Link
[50] LeafGAN: An Effective Data Augmentation Method for Practical Plant Disease Diagnosis, Quan Huu Cap, Hiroyuki Uga, Satoshi Kagiwada and Hitoshi Iyatomi, IEEE Trans. Automation Science and Engineering, Dec. 2020 DOI: 10.1109/TASE.2020.3041499 (in press - early access).
[49] (In Japanese) 植物病害自動診断技術の動向と課題, 彌冨 仁、日本神経回路学会誌, Vol.26, No.4, pp.123-134, 2019.（解説論文）PDF(5.97MB)
[48] Practical plant diagnosis system for field leaf images and feature visualization, Erika Fujita, Hiroyuki Uga, Satoshi Kagiwada, and Hitoshi Iyatomi, International Journal of Engineering & Technology, vol. 7, no. 4.11, pp.49-54, 2018. PDF(441KBytes)
[47] An end-to-end practical plant disease diagnosis system for wide-angle cucumber images, Huu Quan Cap, Katsumasa Suwa, Erika Fujita, Satoshi Kagiwada, Hiroyuki Uga, and Hitoshi Iyatomi, International Journal of Engineering & Technology, vol.7, no.4.11, pp.106-111, 2018. PDF(753KBytes)
[46] (In Japanese) 畳み込みニューラルネットワークを使った授業映像中の聴講者の状態推定システムの構築と特徴量獲得に関する検討, 島田大樹、彌冨 仁、日本知能情報ファジィ学会誌, No.1, pp.517-526, 2017. PDF(6.1 MBytes)
[45] (In Japanese) キュウリウイルス病の画像による診断システムの開発、宇賀博之、彌冨 仁、川崎雄介、藤田恵梨香、鍵和田 聡、植物防疫, Vol.70, No.5, pp.315-318, 2016. PDF(401KBytes)
[44] Four-class classification of skin lesions with task decomposition strategy, Kouhei Shimizu, Hitoshi Iyatomi, M. Emre Celebi, Kerri-Ann Norton, and Masaru Tanaka, IEEE Trans. on Biomedical Engineering, Vol.62, No.1, pp.274-283, 2015. PDF(767KBytes)
[43] An ensemble classification approach for melanoma diagnosis, Gerald Schaefer, Bartosz Krawczyk, M. Emre Celebi and Hitoshi Iyatomi, Memetic computing journal, Vol.6, pp.233-240, 2014. PDF(667KBytes)
[42] Melanoma Classification based on Ensemble Classification of Dermoscopy Image Features, Gerald Schaefer, Bartosz Krawczyk, M. Emre Celebi and Hitoshi Iyatomi and Aboul Ella Hassanien, Advanded Machine Learning and Applications Communications, Vol.488, pp.291-298, 2014. PDF(1.2MBytes)
[41] Age-related prevalence of dermatoscopic patterns of acral melanocytic nevi, Reiko Suzaki, Sumiko Ishizaki, Hitoshi Iyatomi and Masaru Tanaka, Dermatology Practical & Conceptual, Vol.4, No.1, pp.53-57, 2014. PDF(1.7MBytes)
[40] Extension of automated melanoma screening for non-melanocytic skin lesions, Kohei Shimizu, Hitoshi Iyatomi, M.Emre Celebi and Kerri-Ann Norton, International Journal of Intelligent Systems Technologies and Applications, Vol.50, No.1-2, pp.122-130,2014. PDF(299KBytes)
[39] (In Japanese) 非侵襲自律神経疾患計測のための外乱に強い電子瞳孔計の開発, 鬼山 勝、彌冨 仁、尾川浩一、電子情報通信学会論文誌D-I, Vol.86, No.4, pp.867-875, 2013. PDF(2.2MBytes)
[38] Lesion border detection in dermoscopy images using ensembles of thresholding methods, M.Emre.Celebi, Quan Wen, Sae Hwang, Hitoshi Iyatomi and Gerald Schaefer, Skin Research and Technology, Vol.19, No.1, pp.252-258, 2013. PDF(2.2MBytes)
[37] Motion detection system accelerated by GPU for stereotactic radiosurgery, Takuya Yamakawa, Koichi Ogawa, Hitoshi Iyatomi, Etsuo Kunieda, Keisuke Usui, Naoyuki Shigematsu, Medical Imaging Technology, Vol.30, No.5, pp.268-278, 2012.
[36] An Automated Reconstruction Algorithm for Identification of 3D Architectures of Cribriform Ductal Carcinoma in Situ, Kerri-Ann Norton, Sameera Namazi, Nicola Barnard, Mariko Fujibayashi, Gyan Bhanot, Shridar Ganesan, Hitoshi Iyatomi, Koichi Ogawa, and Troy Shinbrot, PLoS ONE, Vol.7, No.9, e44011, Sep. 2012. PDF(756KBytes)
[35] Three-phase general border detection method for dermoscopy images using non-uniform illumination correction, Kerri-Ann Norton, Hitoshi Iyatomi, M. Emre Celebi, Mizuki Sawada, Sumiko Ishizaki, Reiko Suzaki, Ken Kobayashi, Masaru Tanaka and Koichi Ogawa, Skin Research and Technology, Vol.18, No.3, pp.290-300, 2012. PDF(390KBytes)
[34] (In Japanese) 褥瘡重傷度と全身的予後の関係および臨床検査値と褥瘡予後の関係-1,134件の統計的検討,
石崎純子、彌冨 仁、町屋千鶴子、田中 勝,
東京女子医科大学雑誌, Vol.81, No.2, pp.96-101, 2011年4月.
[33] Automated color calibration method for dermoscopy images, Hitoshi Iyatomi, M.Emre Celebi, Gerald Schaefer, Masaru Tanaka, Computerized Medical Imaging and Graphics, Vol.35, No.2, pp.89-98, 2011. PDF(1.6MBytes)
[32] Colour and contrast enhancement for improved skin lesion segmentation, Gerald Schaefer, Maher I. Rajab, M. Emre Celebi, Hitoshi Iyatomi, Computerized Medical Imaging and Graphics, Vol35, No.2, pp.99-104, 2011.
[31] Image analysis for senile lentigo and evaluation of therapeutic effects by hydroquinone, Mizuki SAWADA, Hitoshi IYATOMI, Yoshifumi MAUMI, Ken KOBAYASHI, Reiko SUZAKI, Sumiko ISHIZAKI, Masaru TANAKA, Journal of Investigative Dermatology, Vol.140, p.60, 2010.
[30] Quantitative and objective area extraction of tinea unguium, Yasuki HATA, Hitoshi IYATOMI, Sumiko ISHIZAKI, Mizuki SAWADA, Ken KOBAYASHI, Masahiko OZEKI and Masaru TANAKA, Journal of Investigative Dermatology, Vol.140, p.59, 2010.
[29] Computerized quantification of psoriasis lesions with color calibration: Preliminary results, Hitoshi Iyatomi, Hiroshi Oka, Masafumi Hagiwara, Ayako Miyake, Masayuki Kimoto, Koichi Ogawa and Masaru Tanaka, Clinical and Experimental Dermatology, Vol.34, No.7, pp.830-833, 2009. PDF(258KB)
[28] (In Japanese) 劣化の少ない2値画像回転手法, 彌冨 仁、尾川浩一, 電子情報通信学会論文誌D-II, Vol.92, No.9, pp.1682-1685, 2009.
[27] An Improved Objective Evaluation Measure for Border Detection in Dermoscopy Images, M. Emre Celebi, Gerald Schaefer, Hitoshi Iyatomi, William V. Stoecker, Joseph M. Malters, and James M. Grichnik, Skin Research and Technology, Vol. 15, No.4, pp.444-450, 2009.
[26] Approximate Lesion Localization in Dermoscopy Images, M. Emre Celebi, Hitoshi Iyatomi, Gerald Schaefer, and William V. Stoecker, Skin Research and Technology, Vol. 15, No.3, pp.314-322, 2009.
[25] (In Japanese) ダーモスコピーによる自動診断法, 田中勝、彌冨 仁,
MB Derma, Vol.149, pp.76-82, 2009.
[24] Lesion Border Detection in Dermoscopy Images, M. Emre Celebi, Hitoshi Iyatomi, Gerald Schaefer, and William V. Stoecker, Computerized Medical Imaging and Graphics, Vol.33, No.2, pp.148-153, 2009.
[23] Automatic Detection of Blue-White Veil and Related Structures in Dermoscopy Images, M. Emre Celebi, Hitoshi Iyatomi, William V Stoecker, Randy H Moss, Harold S Rabinovitz, Giuseppe Argenziano, Peter Soyer, Computerized Medical Imaging and Graphics, Vol.32, No.8, pp.670-677, 2008 Online abstract available (link to Pubmed.)
[22] Application of Support Vector Machine Classifiers to Preoperative Risk Stratification with Myocardial Perfusion Scintigraphy, Tomotaka Kasamatsu, Jun Hashimoto, Hitoshi Iyatomi,Tadaki Nakahara, Jingming Bai, Naoto Kitamura, Koichi Ogawa, Atsushi Kubo, Circulation Journal, Vol.72, No.11, pp.1829-1835, 2008. On line abstract available (link to Pubmed.)
[21] Reply to "Digital dermoscopy analysis and internet-based program for discrimination of pigmented skin lesion dermoscopic images,
M.Kimoto, M.Sakamoto, H.Iyatomi and M.Tanaka., Dermatology, Vol.217, No.4, pp.359, 2008. On line version available (link to Karger.com)
[20] An Improved Internet-based Melanoma Screening System with Dermatologist-like Tumor Area Extraction Algorithm, Hitoshi Iyatomi, Hiroshi Oka, M.Emre Celebi, Masahiro Hashimoto, Masafumi Hagiwara, Masaru Tanaka, Koichi Ogawa, Computerized Medical Imaging and Graphics, Vol.32, No.7, pp.566-579, 2008. PDF (1084KBytes)
[19] Computer-based classification of dermoscopy images of melanocytic lesions on acral volar skin Hitoshi Iyatomi, Hiroshi Oka, M Emre Celebi, Koichi Ogawa, Giuseppe Argenziano, H Peter Soyer, Hiroshi Koga, Toshiaki Saida, Kuniaki Ohara, and Masaru Tanaka, Journal of Investigative Dermatology, Vol.128, pp.2049-2054, 2008. PDF (130KBytes)
[18] (In Japanese) 非心臓手術の心事故リスクの推定 －核医学検査の有用性の検討, 彌冨 仁、白 景明、笠松 智孝、橋本 順, 日本知能情報ファジィ学会誌 (医用システム特集号) Vol.20, No.1, pp.100-107, 2008.
[17] Three dimensional melanin distribution of acral melanocytic nevi is reflected in dermoscopy features: Analysis of parallel pattern, M.Kimoto, M.Sakamoto, H.Iyatomi and M.Tanaka. Dermatology, Vol.216, pp.205-212, 2008. Online abstract Available (link to Pubmed.)
[16] Border Detection in Dermoscopy Images Using Statistical Region Merging, M. Emre Celebi, Hassan A. Kingravi,Hitoshi Iyatomi, Y. Alp Aslandogan, William V. Stoecker, Randy H.Moss et al, Skin Research and Technology, Vol.14, Issue 3, pp.347-353, 2008.
[15] A methodological approach to the classification of dermoscopy images, M. Emre Celebi, Hassan A. Kingravi, Bakhtiyar Uddin, Hitoshi Iyatomi, Y. Alp Aslandogan, William V. Stoecker and Randy H.Moss, Computerized Medical Imaging & Graphics, Vol.31, No.6, pp.362-373, 2007.
[11] Reply to "Digital dermoscopy analysis and internet-based program for discrimination of pigmented skin lesion dermoscopic images, Oka H, Iyatomi H, Hashimoto M and Tanaka M, British Journal of Dermatology, Vol.154, No.3, pp.570-571, 2006 Online abstract Available (link to Pubmed.)
[10] (In Japanese) 悪性黒色腫とクラーク母斑のダーモスコピー画像におけるDotsのコンピュータを用いた検出と評価, 吉野寿美、岡博史、田中勝、彌富仁、橋本正弘、本山比佐夫, Skin cancer, Vol.20, No.2, pp.183-189, 2005.
[9] (In Japanese) 悪性黒色腫のダーモスコピー画像における特有色のコンピュータ解析による検出, 本山比佐夫、岡博史、田中勝、彌富仁、橋本正弘、吉野寿美, Skin cancer, Vol.20, No.2, pp.190-196, 2005.
[8] (In Japanese) 掌足庶の病変を含むメラノーマとクラーク母斑のニューラルネットワークを用いた自動判別サーバ, 橋本正弘、岡博史、田中勝、彌富仁、本山比佐夫、吉野寿美, Skin cancer, Vol.20, No.2, pp.197-202, 2005.
[7] (In Japanese) 追加学習可能なファジィ推論ニューラルネットワークの提案と画像認識への応用,
居谷 道明、彌富 仁、萩原将文,
日本知能情報ファジィ学会論文誌 Vol.17, No.1, pp.60-67, 2005.
[6] Adaptive Fuzzy Inference Neural Network, Hitoshi Iyatomi and Masafumi Hagiwara, Pattern Recognition, Vol 37, issue 10, pp.2049-2057, 2004. abstract (link to Elsevier science)/PDF (166KBytes)
[5] (In Japanese) 悪性黒色腫自動診断システムのためのダーモスコピー像からの腫瘍領域抽出法, 彌冨 仁、岡 博史、橋本 正弘、田中 勝、萩原 将文、尾川 浩一, Medical Imaging Technology, Vol.22, No.4, pp.197-200, 2004. PDF (406KB)
[4] Internet-based program for automatic discrimination of dermoscopic images between melanomas and Clark nevi, Oka H, Hashimoto M, Iyatomi H, Argenziano G, Soyer HP and Tanaka M, British Journal of Dermatology No.150, issue 5, p.1041, 2004. abstract (link to PubMed)
[3] (In Japanese) 適応ファジィニューラルネットワークとアクティブ探索法を用いた画像認識, 彌冨 仁、萩原将文 電子情報通信学会論文誌 D-II,Vol.J87-D2, No.4, pp.958-966, 2004. PDF (742KBytes)
[2] Scenery Image Recognition and Interpretation using Fuzzy Inference Neural Networks, Hitoshi Iyatomi and Masafumi Hagiwara, Pattern Recognition Vol.35, issue 8, pp.1793-1806, 2002. PDF (522KBytes)
[1] (In Japanese) ファジィ推論ニューラルネットワークを用いた風景画像からの知識抽出と認識, 彌冨 仁、萩原将文 電子情報通信学会論文誌 D-II Vol.J82-D-II No.4 pp.685-693, 1999. PDF (In Japanese: 269KB)
[93] Extended Japanese Commonsense Morality Dataset with Masked Token and Label Enhancement, Ohashi Takumi, Tsubasa Nakagawa, and Hitoshi Iyatomi, Proc. 33rd ACM International Conference on Information & Knowledge Management (CIKM2024), Oct. 2024. (accepted)
[92] Hierarchical Object Detection and Recognition Framework for Practical Plant Disease Diagnosis, Kohei Iwano, Shogo Shibuya, Satoshi Kagiwada, Hitoshi Iyatomi, Proc. IEEE International Conference on Agrosystem Engineering, Technology & Applications (IEEE AGRETA2024), Sep. 2024. (accepted) arXiv preprint
[91] Majority or Minority: Data imbalance learning method for named entity recognition, Sota Nemoto, Shunsuke Kitada, and Hitoshi Iyatomi, Proc. International Conference on Learning Representations (PMLR4RS - ICLR2024 workshop), May. 2024. Link
[90] A Rapid Deep Learning Approach to Parcellate 280 Anatomical Regions to Cover the Whole Brain, Kei Nishimaki, Kengo Onda, Kunpei Ikuta, Yuto Uchida, Susumu Mori, Hitoshi Iyatomi, and Kenichi Oishi, 2024 ISMRM & ISMRT annual meeting and exhibition, May. 2024
[89] Isometric feature embedding for content-based image retrieval , Hayato Muraki, Kei Nishimaki, Shuya Tobaru, Kenichi Oishi, and Hitoshi Iyatomi, Proc. Information Sciences and Systems (CISS2024), Mar. 2024. (accepted)
[88] Acquiring a low-dimensional, environment-independent representation of brain MR images for content-based image retrieval, Shuya Tobari, Kenichi Oishi, Hitoshi Iyatomi, Proc. IEEE System, Man, and Cybernetics (IEEE SMC2023), pp. 5096-5101, 2023. PDF(649KB)
[87] How are negative articles consumed? A quantitative analysis of user behavior in a real news service?, Kazuya Ohata, Hitoshi Iyatomi, Hajime Morita, Kojiro Iizuka, Proc. IEEE System, Man, and Cybernetics (IEEE SMC2023), pp. 5311-5316, 2023.PDF(685KB)
[86] Feedback is needed for retakes: An explainable poor image notification framework, Kazuya Ohata, Shunsuke Kitatda, and Hitoshi Iyatomi, Proc. IEEE International Conference on Smart Communities: Improving Quality of Life Using ICT. IoT and AI (IEEE HONET2022), pp.166-171, Dec. 2022 Link
[85] Expressions Causing Differences in Emotion Recognition in Social Networking Service Documents , Tsubasa Nakagawa, Shunsuke Kitada, and Hitoshi Iyatomi, Proc. 31st ACM International Conference on Information & Knowledge Management (CIKM2022), pp.4349-4353, Oct. 2022. Link
[84] Loc-VAE: Learning Structurally Localized Representation from 3D Brain MR Images for Content-Based Image Retrieval, Kei Nishimaki, Kumpei Ikuta, Yuto Onga, Hitoshi Iyatomi, and Kenichi Oishi, Proc. IEEE System, Man, and Cybernetics (IEEE SMC2022), pp. 2433-2438, Oct. 2022. Link
[83] Key area acquisition training for practical image-based plant disease diagnosis, Kaito Odagiri, Shogo Shibuya, Quan Huu Cap, and Hitoshi Iyatomi, Proc. IEEE Signal Processing and its Applications (IEEE CSPA 2022), pp.277-282, May. 2022. PDF(12.5MB), Link
[82] Super-resolution for Brain MR Images from a Significantly Small Amount of Training Data, Kumpei Ikuta, Hitoshi Iyatomi, and Kenichi Oishi, Proc. AAAI conference on artificial intelligence, Feb. 2022. Link
[81] Validation of Prerequisites for Correct Performance Evaluation of Image-based Plant Disease Diagnosis using Reliable 221K Images Collected from Actual Fields, Shogo Shibuya, Quan Huu Cap, Shunta Nagasawa, Satoshi Kagiwada, Hiroyuki Uga, and Hitoshi Iyatomi, Proc. AAAI conference on artificial intelligence, (accepted) Feb. 2022. Link
[80] Validity-Based Sampling and Smoothing Method for Multiple Reference Image Captioning, Shunta Nagasawa, Yotaro Watanabe and Hitoshi Iyatomi, 2021 Annual Conference of the North American Chapter of the Association for Computational Linguistics (NAACL2021), pp.36-41, Jun. 2021.Link
[79] Bulk Production Augmentation Towards Explainable Melanoma Diagnosis, Kasumi Obi, Quan Huu Cap, Noriko Umegaki-Arao, Masaru Tanaka, and Hitoshi Iyatomi, Proc. IEEE EMBC Conferences on Biomedical Engineering and Science (IEEE IECBES2020), pp.454-459, Mar. 2021. Student Best Paper Award arXiv PDF(2.26MB)
[78] PPIG: Productive and Pathogenic Image Generation for Plant Disease Diagnosis, Satoi Kanno, Shunta Nagasawa, Quan Huu Cap, Hiroyuki Uga, Satoshi Kagiwada, and Hitoshi Iyatomi, Proc. IEEE EMBC Conferences on Biomedical Engineering and Science (IEEE IECBES2020), pp.554-559, Mar. 2021. PDF (3.24MB)
[77] MIINet: An Image Quality Improvement Framework for Supporting Medical Diagnosis, Quan Huu Cap, Hitoshi Iyatomi and Atsushi Fukuda, International Workshop on Artificial Intelligence for Healthcare Applications (ICPR Workshop 2020), Jan. 2021 Link, arXiv
[76] Text Classification through Glyph-aware Disentangled Character Embedding and Semantic Sub-character Augmentation, Takumi Aoki, Shunsuke Kitada, and Hitoshi Iyatomi, Proc. Asia-Pacific Chapter of the Association for Computational Linguistics and the 10th International Joint Conference on Natural Languate Processing (AACL-IJCNLP2020): student research workshop, Dec. 2020. Link arXiv preprint arXiv:2011.04184
[75] AraDIC: Arabic Document Classification Using Image-Based Character Embeddings and Class-Balanced Loss, Mahmoud Daif, Shunsuke Kitada, and Hitoshi Iyatomi, Proc. 2020 Annual Conference of the Association for Computational Linguistics (ACL2020): student research workshop, pp.214-221, Jul. 2020. PDF (363KB)
[A3] LeafGAN: An Effective Data Augmentation Method for Practical Plant Disease Diagnosis, Quan Huu Cap, Hiroyuki Uga, Satoshi Kagiwada and Hitoshi Iyatomi, Feb. 2020, arXiv preprint arXiv:2002.10100
[74] Efficient feature embedding of 3D brain MRI images for content-based image retrieval with deep metric learning, Yuto Onga, Shingo Fujiyama, Hayato Arai, Yusuke Chayama, Hitoshi Iyatomi, and Kenichi Oishi, Proc. IEEE BigData2019, (Advances in High Dimensional Big Data (AdHD)) , pp.3764-3769, Dec. 2019. PDF(772KB)
[73] Towards Explainable Melanoma Diagnosis: Prediction of Clinical Indicators using Semi-supervised and Multi-task Learning, Seiya Murabayashi and Hitoshi Iyatomi, Proc. IEEE BigData2019, (6th International Workshop on Big Data Analytic Technology for Bioinformatics and Health Informatics (KDDBHI 2019)) , pp. 4853-4857, Dec. 2019. PDF(519KB)
[72] Stochastic Gastric Image Augmentation for Cancer Detection from X-ray Images, Hideaki Okamoto, Quan Huu Cap, Takakiyo Nomura, Hitoshi Iyatomi, and Jun Hashimoto, Proc. IEEE BigData2019, (6th International Workshop on Big Data Analytic Technology for Bioinformatics and Health Informatics (KDDBHI 2019)) , pp. 4858-4663, Dec. 2019. PDF(1.71MB)
[71] AOP: An Anti-overfitting Pretreatment for Practical Image-based Plant Diagnosis, Takumi Saikawa, Quan Huu Cap, Satoshi Kagiwada, Hiroyuki Uga, and Hitoshi Iyatomi, Proc. IEEE BigData2019, (Big Food and Nutrition Data Management and Analysis (BFNDMA 2019)), pp. 5177-5182, Dec. 2019. PDF(2.84MB)
[70] A comparable study: Intrinsic difficulties of practical plant diagnosis from wide-angle images, Katsumasa Suwa, Quan Huu Cap, Ryunosuke Kotani, Hiroyuki Uga, Satoshi Kagiwada, and Hitoshi Iyatomi, Proc. IEEE BigData2019, (Big Food and Nutrition Data Management and Analysis (BFNDMA 2019)), pp. 5195-5201, Dec. 2019. PDF(7.61MB)
[69] Conversion Prediction using Multi-task Conditional Attention Networks to Support the Creation of Effective Ad Creatives, Shunsuke Kitada, Hitoshi Iyatomi, and Yoshifumi Seki, Proc. 25th ACM SIGKDD conference on Knowledge Discovery and Data Mining (KDD2019), Aug. 2019. PDF (1.32MB)
[68] Super-resolution for practical automated plant disease diagnosis system , Huu Quan Cap, Hiroki Tani, Hiroyuki Uga, Satoshi Kagiwada, and Hitoshi Iyatomi, Proc. Information Sciences and Systems (CISS2019), Mar. 2019. PDF (562KB)
[67] End-to-End Text Classification via Image-based Embedding using Character-level Networks, Shunsuke Kitada, Ryunosuke Kotani and Hitoshi Iyatomi, Proc. IEEE Applied Imagery Pattern Recognition (IEEE AIPR 2018), Oct. 2018. PDF (1.59MB)
[66] Diagnosis of Multiple Infections of Cucumber with Convolutional Neural Networks, Hiroki Tani, Satoshi Kagiwada, Hiroyuki Uga and Hitoshi Iyatomi, Proc. IEEE Applied Imagery Pattern Recognition (IEEE AIPR 2018), Oct. 2018. PDF(3.43MB)
[65] Practical plant diagnosis system for field leaf images and feature visualization, Erika Fujita, Hiroyuki Uga, Satoshi Kagiwada, and Hitoshi Iyatomi, Proc. International Symposium on Computational Intelligence and Application (ISCIA2018), Jul. 2018.
[64] An end-to-end practical plant disease diagnosis system for wide-angle cucumber images, Huu Quan Cap, Katsumasa Suwa, Erika Fujita, Satoshi Kagiwada, Hiroyuki Uga, and Hitoshi Iyatomi, Proc. International Symposium on Computational Intelligence and Application (ISCIA2018), Jul. 2018. Best Paper Award
[63] Significant Dimension Reduction of 3D Brain MRI using 3D Convolutional Autoencoders, Hayato Arai, Yusuke Chayama, Hitoshi Iyatomi, and Kenichi Oishi, Proc IEEE Biomedical Engineering (IEEE EMBC 2018), pp.5162-5165, Jul.2018. PDF(1.49MB)
[62] One-dimensional Convolutional Neural Network for Android Malware Detection, Chihiro Hasegawa and Hitoshi Iyatomi, Proc. IEEE Signal Processing and its Applications (IEEE CSPA 2018), pp.101-104, Mar. 2018. PDF(97KB)
[61] Web Application Firewall using Character-level Convolutional Neural Network, Michiaki Ito and Hitoshi Iyatomi, Proc. IEEE Signal Processing and its Applications (IEEE CSPA 2018), pp.105-108, Mar. 2018. PDF (130KB) Best Paper Award
[60] A Deep Learning Approach for on-site Plant Leaf Detection, Quan Huu Cap, Erika Fujita, Satoshi Kagiwada, Hiroyuki Uga, and Hitoshi Iyatomi, Proc. IEEE Signal Processing and its Applications (IEEE CSPA 2018), pp.120-123, Mar. 2018. PDF(549KB)
[59] Basic Investigation on a Robust and Practical Plant Diagnostic System, Erika Fujita, Yusuke Kawasaki, Hiroyuki Uga, Satoshi Kagiwada and Hitoshi Iyatomi, Proc. IEEE Machine Learning and its Applications (IEEE ICMLA 2016), pp.989-992, Dec. 2016. PDF(196KB)
[58] Document Classification through Image-Based Character Embedding and Wildcard Training, Daiki Shimada, Ryunosuke Kotani and Hitoshi Iyatomi, Proc. IEEE BigData 2016 ( Big Data and Natural Processing Workshop (BigNLP 2016), pp.3922-3927, Dec. 2016. PDF(600KB)
[57] Simple and Effective Pre-processing for Automated Melanoma Discrimination based on cytological findings, Takuya Yoshida, M.Emre Celebi, Gerald Scahefer and Hitoshi Iyatomi, Proc. IEEE BigData 2016 (3rd Big Data Analytic Technology for Bioinformatics and Health Informatics (KDDBHI), pp.3439-3442, Dec. 2016. PDF(255KB)
[56] Protptype of super-resolution camera-array system, Daiki Hirao and Hitoshi Iyatomi, Lectures Notes in Computer Science, Vol. 9474, Vol. 1, pp.911-920, Dec. 2015. (International Symposium on Visual Computing 2015 (ISVC2015)), Dec. 2015. PDF(382KB)
[55] Automated habit detection system: A feasibility study, Hiroki Misawa, Takashi Obara and Hitoshi Iyatomi, Lectures Notes in Computer Science, Vol. 9475, Vol. 2, pp.16-23, Dec. 2015. (International Symposium on Visual Computing 2015 (ISVC2015)), Dec. 2015. PDF(734KB)
[54] Building of the readable decision trees for automated melanoma discrimination, Keiichi Ohki, M.Emre Celebi, Gerald Schaefer and Hitoshi Iyatomi, Lectures Notes in Computer Science, Vol. 9475, Vol. 2, pp.712-721, Dec. 2015. (International Symposium on Visual Computing 2015 (ISVC2015)), Dec 2015. PDF(898KB)
[53] Basic Study of Automated Diagnosis of Viral Plant Diseases with Convolutional Neural Networks, Yusuke Kawasaki, Hiroyuki Uga, Satoshi Kagiwada, and Hitoshi Iyatomi, Lectures Notes in Computer Science, Vol. 9475, Vol. 2, pp.638-645, Dec. 2015. (International Symposium on Visual Computing 2015 (ISVC2015)), Dec. 2015. PDF(913KB)
[52] Automated image registration and color calibration of dermoscopy images during the clinical follow-up, Hitoshi Iyatomi, Daiji Furusho, Itaru Dekio and Masaru Tanaka, Proc. 4th World Congress of Dermoscopy and Skin Imaging, Apr. 2015. PDF (2.01MB)
[51] Dermoscopic follow-up of 16 cases of regressing Spitz nevi, Itaru Dekio, Hitoshi Iyatomi, Mizuki Sawada, Sumiko Ishizaki and Masaru Tanaka, Proc. 4th World Congress of Dermoscopy and Skin Imaging, Apr. 2015.
[50] Feasibility study on evaluation of audience’s concentration in the classroom with deep convolutional neural networks, Ryosuke Yoshihashi, Daiki Shimada, Hitoshi Iyatomi, Proc. IEEE Teaching, Assessment and Learning for Engineering (IEEE TALE 2014), Dec. 2014. PDF(461KB)
[49] Accurate discrimination of Alzheimer's disease from other dementia and/or normal sujects using SPECT specific volume analysis, Hitoshi Iyatomi, Jun Hashimoto, Fumihito Yoshii, Toshiki Kazama, Shuichi Kawada and Yutaka Imai, Proc. SPIE Medical Imaging Conference 2014, Vol.9035, doi:10.1117/12.2044011, Feb. 2014. PDF(107KB)
[48] A preliminary study for fully automated quantification of paoriasis severity using image mapping, Kazuhiro Mukai and Hitoshi Iyatomi, Proc. SPIE Medical Imaging Conference 2014, Vol.9035, doi: 10.1117/12.2043446, Feb. 2014. PDF(418KB)
[47] Preliminary experiments on quantification of skin condition, Kenzo Kitajima and Hitoshi Iyatomi, Proc. SPIE Medical Imaging Conference 2014, Vol.9037, doi: 10.1117/12.2044018, Feb. 2014. PDF(271KB)
[46] Registration and color calibration for dermoscopy images in time-course analysis, Daiji Furusho and Hitoshi Iyatomi, Proc. SPIE Medical Imaging Conference 2014, Vol.9035, doi: 10.1117/12.2044019, Feb. 2014. PDF(441KB)
[45] Melanoma classification using dermoscopy imaging and ensemble learning, Gerald Schaefer, Bartosz Krawczyk, M. Emre Celebi and Hitoshi Iyatomi, Proc. 2nd IAPR Asian Conference on Pattern Recognition (ACPR2013), pp.386-390, Nov. 2013.
[44] Production of the grounds for melanoma classification using adaptive fuzzy inference neural network, Yuji Ikuma and Hitoshi Iyatomi, Proc IEEE System, Man and Cybernetics (SMC2013), pp.2570-2575, Oct. 2013. PDF(1.0MB)
[43] 3D Architecture of Ductal Carcinoma in Situ From Image Reconstructions, Kerri-Ann Norton, Sameera Namazi, Nicola Barnard, Mariko Fujibayashi, Gyan Bhanot, Shridar Ganesan, Hitoshi Iyatomi, Koichi Ogawa, and Troy Shinbrot, Proc. IEEE EMBS Conference on Biomedical Engineering (IECBES 2012), pp.631-635, Dec.2012. PDF(56KB)
[42] Development of Robust Video-oculography System for Non-invasive Autonomic Nerve Quantification Masaru Kiyama, Hitoshi Iyatomi and Koichi Ogawa, Proc. IEEE EMBS Conference on Biomedical Engineering (IECBES 2012), pp.853-856, Dec.2012. PDF(1.12MB)
[41] Extension of automated melanoma screening for non-melanocytic skin lesions Kohei Shimizu, M.Emre Celebi, Kerri-Ann Norton and Hitoshi Iyatomi, Proc. 19th International Conference on Mechatronics and Machine Vision in Practice (M2VIP12), pp.16-19, Nov. 2012.
[40] Robust Video-oculography for Non-invasive Autonomic Nerve Quantification Masaru Kiyama, Hitoshi Iyatomi, Koichi Ogawa Proc. IEEE International Conference of the Engineering in Medicine and Bilology Society (EMBS 2011), pp.494-497, 2011.PDF(516KB)
[39] Feasibility Evaluation of a Motion Detection System with Face Images for Stereotactic Radiosurgery Takuya Yamakawa, Koichi Ogawa, Hitoshi Iyatomi, Etsuo Kunieda Proc. IEEE International Conference of the Engineering in Medicine and Bilology Society (EMBS 2011), pp.425-428, 2011.
[38] Automated color normalization for dermoscopy Images Hitoshi Iyatomi, M. Emre Celebi, Gerald Schaefer, Masaru Tanaka Proc. IEEE International Conference on Image Processing (ICIP 2010), Hong Kong, China, pp.4357-4360, Sep. 2010.
[37] Robust border detection in dermosciopy images using threshold fusion, M. Emre Celebi, Sae Hwang, Hitoshi Iyatomi, Gerald Schaefer Proc. IEEE International Conference on Image Processing (ICIP 2010), Hong Kong, China, pp.2541-2544, Sep. 2010.
[36] Quantitative and objective area extraction of tinea unguium Yasuki HATA, Hitoshi IYATOMI, Sumiko ISHIZAKI, Mizuki SAWADA, Ken KOBAYASHI, Masahiko OZEKI and Masaru TANAKA, Journal of Investigative Dermatology, Vol.S140, p.59, Sep. 2010.
[35] Image analysis for senile lentigo and evaluation of therapeutic effects by hydroquinone Mizuki SAWADA, Hitoshi IYATOMI, Yoshifumi MAUMI, Ken KOBAYASHI, Reiko SUZAKI, Sumiko ISHIZAKI, Masaru TANAKA Journal of Investigative Dermatology, Vol.S140, p.60, Sep. 2010.
[34] Skin lesion segmentation using an improved snake model, Huiyu Zhou, Gerald Schaefer, M. Emre Celebi, Hitoshi Iyatomi, Tangwei Liu, Faquan Lin Proc. IEEE International Conference of the Engineering in Medicine and Bilology Society (EMBS 2010), Buenos Aires, Argentina, pp.1974-1977, Aug, 2010.
[33] Classification of melanocytic skin lesions from non-melanocytic lesions, Hitoshi Iyatomi, Kerri-Ann Norton, M. Emre Celebi, Gerald Schaefer, Masaru Tanaka, and Koichi Ogawa Proc. IEEE International Conference of the Engineering in Medicine and Bilology Society (EMBS 2010), Buenos Aires, Argentina, pp.5407-5410, Aug, 2010.
[32] Detection Method for Melanocytic and Non-Melanocytic Dermoscopy Images, Kerri-Ann Norton, Hitoshi Iyatomi, M. Emre Celebi, Gerald Schaefer, Masaru Tanaka, and Koichi Ogawa Proc. IEEE International Conference of the Engineering in Medicine and Bilology Society (EMBS 2010), Buenos Aires, Argentina, pp.5403-5406, Aug, 2010.
[31] Perioperative risk prediction Hitoshi Iyatomi, Tomotaka Kasamatsu, Jun Hashimoto, M.Emre Celebi, Gerald Schaefer and Koichi Ogawa Proc. IEEE International Conference on Information Technology and Applications in Biomedicine (ITAB 2009), Larnaca, Cyprus, pp.1-4, Nov. 2009. PDF(108KB)
[30] Skin lesion segmentation using cooperative neural network edge detection and colour normalisation, Gerald Schaefer, Maher Rajab, M. Emre Celebi and Hitoshi Iyatomi Proc. IEEE International Conference on Information Technology and Applications in Biomedicine (ITAB 2009), Larnaca, Cyprus, pp.1-4, Nov. 2009.
[29] Skin Lesion Extraction in Dermoscopic Images Based on Colour Enhancement and Iterative Segmentation Gerald Schaefer, M. Rajab, M.Emre Celebi, and Hitoshi Iyatomi Proc. IEEE International Conference on Image Processing (ICIP 2009), Cairo, Egypt, pp.3361-3364, Nov. 2009.
[28] Contrast enhancement in dermoscopy images by maximizing a histogram bimodality measure M. Emre Celebi, Hitoshi Iyatomi, Gerald Schaefer Proc. IEEE International Conference on Image Processing (ICIP 2009), Cairo, Egypt, pp.2601-2604, Nov. 2009.
[27]Motion detection system with three USB cameras and an active search algorithm for stereotactic radiosurgery Go Mamiya, Etsuo Kunieda, Yohei Oku, Hitoshi Iyatomi, Koichi Ogawa Proc.11th World Congress on Medical Physics and Biomedical Engineering, Germany, pp.37-40, Sep.2009.
[26] Localization of lesions in dermoscopy images using ensembles of thresholding methods. M.E.Celebi, Hitoshi Iyatomi, Gerald Scheafer, William V.Stoecker, Lectures Note in Computer Science, Vol.5414, pp.1094-1103, Jan.2009.
[25] An analysis of 575 cases of pressure ulcer in a university hospital: correlation between the prognosis of the patients and the severity of their pressure ulcer Sumiko Ishizaki, Hitoshi Iyatomi, Chizuko Machiya, Masaru Tanaka Proceedings of 10th China-Japan joint meeting of Dermatology, Oct.2008.
[24] Development of contactless motion tracking system for stereotactic radiosurgery Go Mamiya, Hitoshi Iyatomi, Koichi Ogawa Proc. 5th Korea-Japan joint meeting on medical physics, Cheju, Korea, SS1-R1-6, Sep.2008.
[23] An Internet-based Melanoma Screening System - Supported Acral Volar Lesions Hitoshi Iyatomi, M.Emre Celebi, Hiroshi Oka, Masaru Tanaka Proc. IEEE EMBC 2008, Vancouver, Canada, pp.5156-5159, Aug.2008. PDF (242KB)
[22] Objective Evaluation of Methods for Border Detection in Dermoscopy Images M.Emre Celebi, Gerald Schaefer, Hitoshi Iyatomi Proc. IEEE EMBC 2008, Vancouver, Canada, pp.3056-3059, Aug.2008. PDF (224KB)
[21] Identification of shot-body-regions from clinical photograph using support vector machine classifiers Hitoshi Iyatomi and Koichi Ogawa Proc. 10th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI 2007 Workshop), Brisbane, Australia, Oct.2007.
[20] Parametric Analysis of Acral Lesions on Dermoscopy Hitoshi Iyatomi, Hiroshi Oka, Masaru Tanaka and Koichi Ogawa Proc. of IEEE CME 2007, Beijin, China, pp.337-340, May.2007. PDF (185KB)
[19] Parameterization of Dermoscopic Findings for the Internet-based Melanoma Diagnostic System Hitoshi Iyatomi, Hiroshi Oka, M.Emre Celebi, Masaru Tanaka and Koichi Ogawa Proc.IEEE CIISP 2007, pp.183-193, Honolulu, Apr.2007. PDF(142KB)
[18] Fast and Accurate Border Detection in Dermoscopy Images Using Statistical Region Merging M. Emre Celebi, Hassan A. Kingravi, Hitoshi Iyatomi, JeongKyu Lee et al. Proc. SPIE Medical Imaging 2007 Conference, Feb.2007.
[17] Classification of Asian-specific acral lesions for internet-based melanoma diagnostic system Hitoshi Iyatomi, Hiroshi Oka, Masaru Tanaka and Koichi Ogawa Proc. Asian Medical Imaging Forum 2007, MI2006-183, pp.95-98, Cheju, Jan. 2007.
[16] Automatic Identification of Shot Body Region from Clinical Photographies Hitoshi Iyatomi, Masahiro Hashimoto, Hiroshi Oka, Masaru Tanaka and Koichi Ogawa Proc. IEEE 35th International Workshop on AIPR 2006, Washington DC, Oct. 2006.
[15] Classification of blue nevus from other lesions for Internet-based melanoma diagnostic system Hitoshi Iyatomi, Yuki Tanahashi, Hiroshi Oka, Masaru Tanaka and Koichi Ogawa Proc. 7th International Symposium on Advanced Intelligent Systems, Tokyo, pp.1995-2000, 2006.
[14] Portable VOG, a new device for on site nystagmus recording N.Ide, E.Sugiura, K.Miyajima, Y.Arai, H.Iyatomi and M.Yamamoto. 24th Barany Society Meeting, Uppsala, Sweden, Jun. 2006
[13] Current state of the Internet-based melanoma screening system Hitoshi Iyatomi, Hiroshi Oka, Masafumi Hagiwara, Masahiro Hashimoto,Koichi Ogawa, Masaru Tanaka First Congress of the International Dermoscopy Society, Naples, p.271, Apr.2006
[12] Hemifacial trial of vitamin C sonophoresis in melasma. Junko Kawashima, Shin-ichi Takahashi, Atsuko Katoh, Masaru Tanaka, Hitoshi Iyatomi, Hiroyuki Takano, Yasuhiro Sato. First Congress of the International Dermoscopy Society, Naples, Apr.27-29, 2006
[11] An Practical Internet-based Melanoma Diagnostic System Hitoshi Iyatomi, Hiroshi Oka, Ayako Miyake, Masayuki Kimoto Masaru Tanaka and Koichi Ogawa Proc. IEEE Symposium on CIBCB, pp.443-446, San Diego USA, Nov.2005. PDF (267KB)
[10] Preliminary study for quantification of psooriasis with color calibration Hitoshi Iyatomi, Hiroshi Oka, Ayako Miyake, Masayuki Kimoto Masaru Tanaka and Koichi Ogawa Proc. 4th Japan-Korea Joint Meeting on Medical Physics and the 5th Asia-Oceania Congress of Medical Physics, Kyoto, Japan, Sep.2005.
[9] Development of contactless motion tracking method for stereotactic radiosurgery Yuta Hojo, Hitoshi Iyatomi and Koichi Ogawa Proc. 4th Japan-Korea Joint Meeting on Medical Physics and the 5th Asia-Oceania Congress of Medical Physics, Kyoto, Japan, Sep.2005.
[8] Practical web-based screening system for early stage of malignant melanoma Hitoshi Iyatomi, Hiroshi Oka, Masaru Tanaka, Masafumi Hagiwara and Koichi Ogawa Proc. 3rd International Conference on Information (INFO2004), Tokyo, Japan, pp.628-631,Nov.2004
[7] Automatic tumor area extraction from dermoscopy image H.Iyatomi, H.Oka, M.Hashimoto, A.Tanikawa, M.Hagiwara and M.Tanaka Journal of European Academy of Dermatology and Venereology, Florence Italy, p.271, Oct.2004
[6] Development of diagnostic system for early stage of malignant melanoma Hitoshi Iyatomi, Hiroshi Oka, Masaru Tanaka and Masafumi Hagiwara Proc.5th International Symposium on Advanced Intelligent Systems, Yokohama, Japan, p.69, WE-4, Sep.2004.
[5] Additional Learning Machine Framework for Multipurpose Image Recognition Michiaki Itani, Hitoshi Iyatomi and Masafumi Hagiwara Proc.4th International Symposium on Advanced Intelligent Systems, Jeju Island, Korea, pp.480-pp.483, Sep.2003.
[4] Digital analysis of dermoscopy with multivariate stepwise discriminant analysis between early Melanoma and Nevi Oka H, Tanaka M, Kobayashi S, Iyatomi H, Hagiwara M, Argenziano G, Soyer H.P. and Nishikawa T. European congress of the EADV, Barcelona, Spain, Oct.2003.
[3] Classification of Reed/Spitz Nevi and Melanomas using digital image processing with linear discriminant analysis Kobayashi S, Tanaka M, Oka H, Iyatomi H, Hagiwara M, Argenziano G, Soyer H.P and Nishikawa T. European congress of the EADV, Barcelona, Spain, Oct.2003.
[2] Adaptive Fuzzy Inference Neural Network Hitoshi Iyatomi and Masafumi Hagiwara Proc. 10th International Conference on Human Computer Interaction 2003, Crete, Greece, Vol.2, pp.400-404.
[1] Knowledge Extraction from Scereny Images and the Recognition using Fuzzy Inference Neural Networks. Hitoshi Iyatomi and Masafumi Hagiwara IEEE International Conference on System Man and Cybernetics, San Diego, USA, pp.4486-4491, Oct.1998. PDF (480KBytes)
[A13] A Neural Network Approach to Identify Left-Right Orientation of Anatomical Brain MRI, Kei Nishimaki, Hitoshi Iyatomi, and Kenichi Oishi, Feb. 2024, bioRxiv 2024.02.15.580574
[A12] Majority of Minority: Data Imbalance Learning Method for Named Entity Recognition, Sota Nemoto, Shunsuke Kitada, and Hitoshi Iyatomi, Jan. 2024, arXiv preprint arXiv:2401.11431
[A11] OpenMAP-T1: A Rapid Deep Learning Approach to Parcellate 280 Anatomical Regions to Cover the Whole Brain, Kei Nishimaki, Kengo Onda, Kunpei Ikuta, Yuto Uchida, Susumu Mori, Hitoshi Iyatomi, and Kenichi Oishi, Jan. 2024 medRxiv 2024.01.18.24301494; doi: https://doi.org/10.1101/2024.01.18.24301494, codes (github)
[A10] Towards Robust Plant Disease Diagnosis with Hard-sample Re-mining Strategy, Quan Huu Cap, Atsushi Fukuda, Satoshi Kagiwada, Hiroyuki Uga, Nobusuke Iwasaki, Hitoshi Iyatomi, Sep. 2023, arXiv preprint arXiv:2309.01903
[A9] Investigation to Answer Three Key Questions Concerning Plant Pest Identification and Development of a Practical Identification Framework, Ryosuke Wayama, Yuki Sasaki, Satoshi Kagiwada, Nobusuke Iwasaki, and Hitoshi Iyatomi, Jul 2023, SSRN pre-print, http://dx.doi.org/10.2139/ssrn.4524872
[A8] A Practical Framework for Unsupervised Structure Preservation Medical Image Enhancement, Quan Huu Cap, Atsushi Fukuda, and Hitoshi Iyatomi, Aug. 2021, arXiv preprint arXiv:2304.01864
[abs] An effective manoeuvre in deep learning techniques to provide multiscale robustness for plant disease diagnosis, Gent Imeraj, Sayo Nishii, Daiki Ito, and Hitoshi Iyatomi,Trends in Nanotechnology2022 (TNT2022), Oct. 2022.
[A7] Gastric Cancer Detection from X-ray Images Using Effective Data Augmentation and Hard Boundary Box Training, Hideaki Okamoto, Takakiyo Nomura, Kazuhito Nabeshima, Jun Hashimoto, and Hitoshi Iyatomi, Aug. 2021, arXiv preprint arXiv:2108.08158
[A6] Disease-oriented image embedding with pseudo-scanner standardization for content-based image retrieval on 3D brain MRI, Hayato Arai, Yuto Onga, Kumpei Ikuta, Hitoshi Iyatomi and Kenichi Oishi, Aug. 2021, arXiv preprint arXiv:2108.06518
[A5] LASSR: Effective Super-Resolution Method for Plant Disease Diagnosis, Quan Huu Cap, Hiroki Tani, Hiroyuki Uga, Satoshi Kagiwada, and Hitoshi Iyatomi, Oct. 2020, arXiv preprint arXiv:2010.06499
[A4] Attention Meets Perturbations: Robust and Interpretable Attention with Adversarial Training, Shunsuke Kitada and Hitoshi Iyatomi, Sept. 2020, arXiv preprint arXiv:2009.12064
[A3] LeafGAN: An Effective Data Augmentation Method for Practical Plant Disease Diagnosis, Quan Huu Cap, Hiroyuki Uga, Satoshi Kagiwada and Hitoshi Iyatomi, Feb. 2020, arXiv preprint arXiv:2002.10100
[A2] End-to-End Text Classification via Image-based Embedding using Character-level Networks, Shunsuke Kitada, Ryunosuke Kotani and Hitoshi Iyatomi, arXiv preprint arXiv:1810.03595
[A1] Skin lesion classification with ensemble of squeeze-and-excitation networks and semi-supervised learning, Shunsuke Kitada and Hitoshi Iyatomi, arXiv preprint arXiv:1809.02568