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Hitoshi Iyatomi
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2020 – today
- 2024
- [j22]Ryosuke Wayama, Yuki Sasaki, Satoshi Kagiwada
, Nobusuke Iwasaki, Hitoshi Iyatomi
:
Investigation to answer three key questions concerning plant pest identification and development of a practical identification framework. Comput. Electron. Agric. 222: 109021 (2024) - [c41]Hayato Muraki, Kei Nishimaki, Shuya Tobari, Kenichi Oishi, Hitoshi Iyatomi:
Isometric Feature Embedding for Content-Based Image Retrieval. CISS 2024: 1-6 - [i32]Sota Nemoto, Shunsuke Kitada, Hitoshi Iyatomi:
Majority or Minority: Data Imbalance Learning Method for Named Entity Recognition. CoRR abs/2401.11431 (2024) - [i31]Kohei Iwano, Shogo Shibuya, Satoshi Kagiwada, Hitoshi Iyatomi:
Hierarchical Object Detection and Recognition Framework for Practical Plant Disease Diagnosis. CoRR abs/2407.17906 (2024) - [i30]Ryosuke Wayama, Yuki Sasaki, Satoshi Kagiwada, Nobusuke Iwasaki, Hitoshi Iyatomi:
Investigation to answer three key questions concerning plant pest identification and development of a practical identification framework. CoRR abs/2407.18000 (2024) - 2023
- [j21]Kei Nishimaki
, Kumpei Ikuta
, Shingo Fujiyama, Kenichi Oishi
, Hitoshi Iyatomi
:
PCSS: Skull Stripping With Posture Correction From 3D Brain MRI for Diverse Imaging Environment. IEEE Access 11: 116903-116918 (2023) - [j20]Shunsuke Kitada
, Hitoshi Iyatomi
:
Making attention mechanisms more robust and interpretable with virtual adversarial training. Appl. Intell. 53(12): 15802-15817 (2023) - [j19]Quan Huu Cap
, Atsushi Fukuda, Satoshi Kagiwada
, Hiroyuki Uga, Nobusuke Iwasaki, Hitoshi Iyatomi:
Towards robust plant disease diagnosis with hard-sample re-mining strategy. Comput. Electron. Agric. 215: 108375 (2023) - [j18]Lei Bi, M. Emre Celebi, Hitoshi Iyatomi, Pablo Fernandez-Penas, Jinman Kim:
Image analysis in advanced skin imaging technology. Comput. Methods Programs Biomed. 238: 107599 (2023) - [c40]Shuya Tobari, Kenichi Oishi, Hitoshi Iyatomi:
Acquiring a Low-Dimensional, Environment-Independent Representation of Brain MR Images for Content-Based Image Retrieval. SMC 2023: 5096-5101 - [c39]Kazuya Ohata, Hitoshi Iyatomi, Hajime Morita, Kojiro Iizuka:
How are Negative Articles Consumed? A Quantitative Analysis of User Behavior in a Real News Service. SMC 2023: 5311-5316 - [i29]Quan Huu Cap, Atsushi Fukuda, Hitoshi Iyatomi:
A Practical Framework for Unsupervised Structure Preservation Medical Image Enhancement. CoRR abs/2304.01864 (2023) - [i28]Quan Huu Cap, Atsushi Fukuda, Satoshi Kagiwada, Hiroyuki Uga, Nobusuke Iwasaki, Hitoshi Iyatomi:
Towards Robust Plant Disease Diagnosis with Hard-sample Re-mining Strategy. CoRR abs/2309.01903 (2023) - 2022
- [j17]Shunsuke Kitada
, Yuki Iwazaki, Riku Togashi, Hitoshi Iyatomi
:
DM2S2: Deep Multimodal Sequence Sets With Hierarchical Modality Attention. IEEE Access 10: 120023-120034 (2022) - [j16]Quan Huu Cap
, Hiroyuki Uga, Satoshi Kagiwada
, Hitoshi Iyatomi
:
LeafGAN: An Effective Data Augmentation Method for Practical Plant Disease Diagnosis. IEEE Trans Autom. Sci. Eng. 19(2): 1258-1267 (2022) - [c38]Tsubasa Nakagawa, Shunsuke Kitada, Hitoshi Iyatomi:
Expressions Causing Differences in Emotion Recognition in Social Networking Service Documents. CIKM 2022: 4349-4353 - [c37]Kei Nishimaki, Kumpei Ikuta, Yuto Onga, Hitoshi Iyatomi, Kenichi Oishi:
Loc-VAE: Learning Structurally Localized Representation from 3D Brain MR Images for Content-Based Image Retrieval. SMC 2022: 2433-2438 - [i27]Shunsuke Kitada, Hitoshi Iyatomi, Yoshifumi Seki:
Ad Creative Discontinuation Prediction with Multi-Modal Multi-Task Neural Survival Networks. CoRR abs/2204.11588 (2022) - [i26]Tsubasa Nakagawa, Shunsuke Kitada, Hitoshi Iyatomi:
Expressions Causing Differences in Emotion Recognition in Social Networking Service Documents. CoRR abs/2208.14244 (2022) - [i25]Shunsuke Kitada, Yuki Iwazaki, Riku Togashi, Hitoshi Iyatomi:
DM2S2: Deep Multi-Modal Sequence Sets with Hierarchical Modality Attention. CoRR abs/2209.03126 (2022) - [i24]Kei Nishimaki, Kumpei Ikuta, Yuto Onga, Hitoshi Iyatomi, Kenichi Oishi:
Loc-VAE: Learning Structurally Localized Representation from 3D Brain MR Images for Content-Based Image Retrieval. CoRR abs/2210.00506 (2022) - [i23]Kazuya Ohata, Shunsuke Kitada, Hitoshi Iyatomi:
Feedback is Needed for Retakes: An Explainable Poor Image Notification Framework for the Visually Impaired. CoRR abs/2211.09427 (2022) - 2021
- [j15]Shunsuke Kitada
, Hitoshi Iyatomi
:
Attention Meets Perturbations: Robust and Interpretable Attention With Adversarial Training. IEEE Access 9: 92974-92985 (2021) - [j14]Hayato Arai, Yuto Onga, Kumpei Ikuta, Yusuke Chayama, Hitoshi Iyatomi
, Kenichi Oishi:
Disease-Oriented Image Embedding With Pseudo-Scanner Standardization for Content-Based Image Retrieval on 3D Brain MRI. IEEE Access 9: 165326-165340 (2021) - [j13]Quan Huu Cap
, Hiroki Tani, Satoshi Kagiwada, Hiroyuki Uga, Hitoshi Iyatomi:
LASSR: Effective super-resolution method for plant disease diagnosis. Comput. Electron. Agric. 187: 106271 (2021) - [i22]Kasumi Obi, Quan Huu Cap, Noriko Umegaki-Arao, Masaru Tanaka, Hitoshi Iyatomi:
Bulk Production Augmentation Towards Explainable Melanoma Diagnosis. CoRR abs/2103.02198 (2021) - [i21]Shunsuke Kitada, Hitoshi Iyatomi:
Making Attention Mechanisms More Robust and Interpretable with Virtual Adversarial Training for Semi-Supervised Text Classification. CoRR abs/2104.08763 (2021) - [i20]Hayato Arai, Yuto Onga, Kumpei Ikuta, Yusuke Chayama, Hitoshi Iyatomi, Kenichi Oishi:
Disease-oriented image embedding with pseudo-scanner standardization for content-based image retrieval on 3D brain MRI. CoRR abs/2108.06518 (2021) - [i19]Hideaki Okamoto, Takakiyo Nomura, Kazuhito Nabeshima, Jun Hashimoto, Hitoshi Iyatomi:
Gastric Cancer Detection from X-ray Images Using Effective Data Augmentation and Hard Boundary Box Training. CoRR abs/2108.08158 (2021) - 2020
- [c36]Mahmoud Daif, Shunsuke Kitada
, Hitoshi Iyatomi:
AraDIC: Arabic Document Classification Using Image-Based Character Embeddings and Class-Balanced Loss. ACL (student) 2020: 214-221 - [c35]Quan Huu Cap, Hitoshi Iyatomi, Atsushi Fukuda:
MIINet: An Image Quality Improvement Framework for Supporting Medical Diagnosis. ICPR Workshops (1) 2020: 254-265 - [c34]Takumi Aoki, Shunsuke Kitada, Hitoshi Iyatomi:
Text Classification through Glyph-aware Disentangled Character Embedding and Semantic Sub-character Augmentation. AACL/IJCNLP (Student Research Workshop) 2020: 1-7 - [i18]Quan Huu Cap, Hiroyuki Uga, Satoshi Kagiwada, Hitoshi Iyatomi:
LeafGAN: An Effective Data Augmentation Method for Practical Plant Disease Diagnosis. CoRR abs/2002.10100 (2020) - [i17]Mahmoud Daif, Shunsuke Kitada, Hitoshi Iyatomi:
AraDIC: Arabic Document Classification using Image-Based Character Embeddings and Class-Balanced Loss. CoRR abs/2006.11586 (2020) - [i16]Shunsuke Kitada, Hitoshi Iyatomi:
Attention Meets Perturbations: Robust and Interpretable Attention with Adversarial Training. CoRR abs/2009.12064 (2020) - [i15]Quan Huu Cap
, Hiroki Tani, Hiroyuki Uga, Satoshi Kagiwada, Hitoshi Iyatomi:
LASSR: Effective Super-Resolution Method for Plant Disease Diagnosis. CoRR abs/2010.06499 (2020) - [i14]Takumi Aoki, Shunsuke Kitada, Hitoshi Iyatomi:
Text Classification through Glyph-aware Disentangled Character Embedding and Semantic Sub-character Augmentation. CoRR abs/2011.04184 (2020) - [i13]Quan Huu Cap
, Hitoshi Iyatomi, Atsushi Fukuda:
MIINet: An Image Quality Improvement Framework for Supporting Medical Diagnosis. CoRR abs/2011.14132 (2020)
2010 – 2019
- 2019
- [c33]Yuto Onga, Shingo Fujiyama, Hayato Arai, Yusuke Chayama, Hitoshi Iyatomi, Kenichi Oishi
:
Efficient feature embedding of 3D brain MRI images for content-based image retrieval with deep metric learning. IEEE BigData 2019: 3764-3769 - [c32]Seiya Murabayashi, Hitoshi Iyatomi:
Towards Explainable Melanoma Diagnosis: Prediction of Clinical Indicators Using Semi-supervised and Multi-task Learning. IEEE BigData 2019: 4853-4857 - [c31]Hideaki Okamoto, Quan Huu Cap
, Takakiyo Nomura, Hitoshi Iyatomi, Jun Hashimoto:
Stochastic Gastric Image Augmentation for Cancer Detection from X-ray Images. IEEE BigData 2019: 4858-4863 - [c30]Takumi Saikawa, Quan Huu Cap
, Satoshi Kagiwada
, Hiroyuki Uga, Hitoshi Iyatomi:
AOP: An Anti-overfitting Pretreatment for Practical Image-based Plant Diagnosis. IEEE BigData 2019: 5177-5182 - [c29]Katsumasa Suwa, Quan Huu Cap
, Ryunosuke Kotani, Hiroyuki Uga, Satoshi Kagiwada
, Hitoshi Iyatomi:
A comparable study: Intrinsic difficulties of practical plant diagnosis from wide-angle images. IEEE BigData 2019: 5195-5201 - [c28]Quan Huu Cap
, Hiroki Tani, Hiroyuki Uga, Satoshi Kagiwada
, Hitoshi Iyatomi:
Super-Resolution for Practical Automated Plant Disease Diagnosis System. CISS 2019: 1-6 - [c27]Shunsuke Kitada
, Hitoshi Iyatomi, Yoshifumi Seki:
Conversion Prediction Using Multi-task Conditional Attention Networks to Support the Creation of Effective Ad Creatives. KDD 2019: 2069-2077 - [i12]Shunsuke Kitada, Hitoshi Iyatomi, Yoshifumi Seki:
Conversion Prediction Using Multi-task Conditional Attention Networks to Support the Creation of Effective Ad Creative. CoRR abs/1905.07289 (2019) - [i11]Katsumasa Suwa, Quan Huu Cap, Ryunosuke Kotani, Hiroyuki Uga, Satoshi Kagiwada, Hitoshi Iyatomi:
A comparable study: Intrinsic difficulties of practical plant diagnosis from wide-angle images. CoRR abs/1910.11506 (2019) - [i10]Takumi Saikawa, Quan Huu Cap, Satoshi Kagiwada, Hiroyuki Uga, Hitoshi Iyatomi:
AOP: An Anti-overfitting Pretreatment for Practical Image-based Plant Diagnosis. CoRR abs/1911.10727 (2019) - [i9]Quan Huu Cap, Hiroki Tani, Hiroyuki Uga, Satoshi Kagiwada, Hitoshi Iyatomi:
Super-Resolution for Practical Automated Plant Disease Diagnosis System. CoRR abs/1911.11341 (2019) - [i8]Yuto Onga, Shingo Fujiyama, Hayato Arai, Yusuke Chayama, Hitoshi Iyatomi, Kenichi Oishi:
Efficient feature embedding of 3D brain MRI images for content-based image retrieval with deep metric learning. CoRR abs/1912.01824 (2019) - 2018
- [c26]Shunsuke Kitada
, Ryunosuke Kotani, Hitoshi Iyatomi:
End-to-End Text Classification via Image-based Embedding using Character-level Networks. AIPR 2018: 1-4 - [c25]Hiroki Tani, Ryunosuke Kotani, Satoshi Kagiwada
, Hiroyuki Uga, Hitoshi Iyatomi:
Diagnosis of Multiple Cucumber Infections with Convolutional Neural Networks. AIPR 2018: 1-4 - [c24]Hayato Arai, Yusuke Chayama, Hitoshi Iyatomi, Kenichi Oishi
:
Significant Dimension Reduction of 3D Brain MRI using 3D Convolutional Autoencoders. EMBC 2018: 5162-5165 - [i7]Shunsuke Kitada, Hitoshi Iyatomi:
Skin lesion classification with ensemble of squeeze-and-excitation networks and semi-supervised learning. CoRR abs/1809.02568 (2018) - [i6]Shunsuke Kitada, Ryunosuke Kotani, Hitoshi Iyatomi:
End-to-End Text Classification via Image-based Embedding using Character-level Networks. CoRR abs/1810.03595 (2018) - 2016
- [c23]Takuya Yoshida, M. Emre Celebi, Gerald Schaefer, Hitoshi Iyatomi:
Simple and effective pre-processing for automated melanoma discrimination based on cytological findings. IEEE BigData 2016: 3439-3442 - [c22]Daiki Shimada, Ryunosuke Kotani, Hitoshi Iyatomi:
Document classification through image-based character embedding and wildcard training. IEEE BigData 2016: 3922-3927 - [c21]Erika Fujita, Yusuke Kawasaki, Hiroyuki Uga, Satoshi Kagiwada, Hitoshi Iyatomi:
Basic Investigation on a Robust and Practical Plant Diagnostic System. ICMLA 2016: 989-992 - 2015
- [j12]Kouhei Shimizu, Hitoshi Iyatomi, M. Emre Celebi
, Kerri-Ann Norton, Masaru Tanaka:
Four-Class Classification of Skin Lesions With Task Decomposition Strategy. IEEE Trans. Biomed. Eng. 62(1): 274-283 (2015) - [c20]Hiroki Misawa, Takashi Obara, Hitoshi Iyatomi:
Automated Habit Detection System: A Feasibility Study. ISVC (2) 2015: 16-23 - [c19]Yusuke Kawasaki, Hiroyuki Uga, Satoshi Kagiwada
, Hitoshi Iyatomi:
Basic Study of Automated Diagnosis of Viral Plant Diseases Using Convolutional Neural Networks. ISVC (2) 2015: 638-645 - [c18]Keiichi Ohki, M. Emre Celebi, Gerald Schaefer, Hitoshi Iyatomi:
Building of Readable Decision Trees for Automated Melanoma Discrimination. ISVC (2) 2015: 712-721 - [c17]Daiki Hirao, Hitoshi Iyatomi:
Prototype of Super-Resolution Camera Array System. ISVC (1) 2015: 911-920 - 2014
- [j11]Kouhei Shimizu, Hitoshi Iyatomi, Kerri-Ann Norton, M. Emre Celebi:
Extension of automated melanoma screening for non-melanocytic skin lesions. Int. J. Comput. Appl. Technol. 50(1/2): 122-130 (2014) - [j10]Gerald Schaefer, Bartosz Krawczyk, M. Emre Celebi
, Hitoshi Iyatomi:
An ensemble classification approach for melanoma diagnosis. Memetic Comput. 6(4): 233-240 (2014) - [c16]Gerald Schaefer, Bartosz Krawczyk, M. Emre Celebi, Hitoshi Iyatomi, Aboul Ella Hassanien:
Melanoma Classification Based on Ensemble Classification of Dermoscopy Image Features. AMLTA 2014: 291-298 - [c15]Daiji Furusho, Hitoshi Iyatomi:
Registration and color calibration for dermoscopy images in time-course analysis. Medical Imaging: Computer-Aided Diagnosis 2014: 90353B - [c14]Kazuhiro Mukai, Hitoshi Iyatomi:
A preliminary study for fully automated quantification of psoriasis severity using image mapping. Medical Imaging: Computer-Aided Diagnosis 2014: 90353N - [c13]Hitoshi Iyatomi, Jun Hashimoto, Fumuhito Yoshii, Toshiki Kazama, Shuichi Kawada, Yutaka Imai:
Accurate discrimination of Alzheimer's disease from other dementia and/or normal subjects using SPECT specific volume analysis. Medical Imaging: Computer-Aided Diagnosis 2014: 903523 - 2013
- [c12]Gerald Schaefer, Bartosz Krawczyk, M. Emre Celebi
, Hitoshi Iyatomi:
Melanoma Classification Using Dermoscopy Imaging and Ensemble Learning. ACPR 2013: 386-390 - [i5]M. Emre Celebi, Quan Wen, Sae Hwang, Hitoshi Iyatomi, Gerald Schaefer:
Lesion Border Detection in Dermoscopy Images Using Ensembles of Thresholding Methods. CoRR abs/1312.7345 (2013) - 2011
- [j9]Hitoshi Iyatomi, M. Emre Celebi
, Gerald Schaefer, Masaru Tanaka:
Automated color calibration method for dermoscopy images. Comput. Medical Imaging Graph. 35(2): 89-98 (2011) - [j8]Gerald Schaefer, Maher I. Rajab, M. Emre Celebi
, Hitoshi Iyatomi:
Colour and contrast enhancement for improved skin lesion segmentation. Comput. Medical Imaging Graph. 35(2): 99-104 (2011) - [c11]Takuya Yamakawa, Koichi Ogawa
, Hitoshi Iyatomi, Etsuo Kunieda:
Feasibility evaluation of a motion detection system with face images for stereotactic radiosurgery. EMBC 2011: 425-428 - [c10]Masaru Kiyama, Hitoshi Iyatomi, Koichi Ogawa
:
Robust video-oculography for non-invasive autonomic nerve quantification. EMBC 2011: 494-496 - 2010
- [c9]M. Emre Celebi
, Sae Hwang, Hitoshi Iyatomi, Gerald Schaefer:
Robust border detection in dermoscopy images using threshold fusion. ICIP 2010: 2541-2544 - [c8]Hitoshi Iyatomi, M. Emre Celebi
, Gerald Schaefer, Masaru Tanaka:
Automated color normalization for dermoscopy images. ICIP 2010: 4357-4360 - [i4]M. Emre Celebi, Hitoshi Iyatomi, William V. Stoecker, Randy H. Moss, Harold S. Rabinovitz, Giuseppe Argenziano, H. Peter Soyer:
Automatic Detection of Blue-White Veil and Related Structures in Dermoscopy Images. CoRR abs/1009.1013 (2010) - [i3]M. Emre Celebi, Gerald Schaefer, Hitoshi Iyatomi, William V. Stoecker, Joseph M. Malters, James M. Grichnik:
An Improved Objective Evaluation Measure for Border Detection in Dermoscopy Images. CoRR abs/1009.1020 (2010) - [i2]M. Emre Celebi, Hitoshi Iyatomi, Gerald Schaefer, William V. Stoecker:
Approximate Lesion Localization in Dermoscopy Images. CoRR abs/1009.1362 (2010) - [i1]M. Emre Celebi, Hitoshi Iyatomi, Gerald Schaefer, William V. Stoecker:
Lesion Border Detection in Dermoscopy Images. CoRR abs/1011.0640 (2010)
2000 – 2009
- 2009
- [j7]M. Emre Celebi
, Hitoshi Iyatomi, Gerald Schaefer, William V. Stoecker:
Lesion border detection in dermoscopy images. Comput. Medical Imaging Graph. 33(2): 148-153 (2009) - [c7]M. Emre Celebi
, Hitoshi Iyatomi, Gerald Schaefer:
Contrast enhancement in dermoscopy images by maximizing a histogram bimodality measure. ICIP 2009: 2601-2604 - [c6]Gerald Schaefer, Maher I. Rajab, M. Emre Celebi
, Hitoshi Iyatomi:
Skin lesion extraction in dermoscopic images based on colour enhancement and iterative segmentation. ICIP 2009: 3361-3364 - [c5]M. Emre Celebi, Hitoshi Iyatomi, Gerald Schaefer, William V. Stoecker:
Localization of Lesions in Dermoscopy Images Using Ensembles of Thresholding Methods. PSIVT 2009: 1094-1103 - 2008
- [j6]Hitoshi Iyatomi, Hiroshi Oka, M. Emre Celebi
, Masahiro Hashimoto, Masafumi Hagiwara, Masaru Tanaka, Koichi Ogawa
:
An improved Internet-based melanoma screening system with dermatologist-like tumor area extraction algorithm. Comput. Medical Imaging Graph. 32(7): 566-579 (2008) - [j5]M. Emre Celebi
, Hitoshi Iyatomi, William V. Stoecker, Randy H. Moss, Harold S. Rabinovitz, Giuseppe Argenziano
, H. Peter Soyer
:
Automatic detection of blue-white veil and related structures in dermoscopy images. Comput. Medical Imaging Graph. 32(8): 670-677 (2008) - 2007
- [j4]M. Emre Celebi
, Hassan A. Kingravi, Bakhtiyar Uddin, Hitoshi Iyatomi, Y. Alp Aslandogan, William V. Stoecker, Randy H. Moss:
A methodological approach to the classification of dermoscopy images. Comput. Medical Imaging Graph. 31(6): 362-373 (2007) - [c4]M. Emre Celebi, Hassan A. Kingravi, Hitoshi Iyatomi, JeongKyu Lee, Y. Alp Aslandogan, William Van Stoecker, Randy H. Moss, Joseph M. Malters, Ashfaq A. Marghoob:
Fast and accurate border detection in dermoscopy images using statistical region merging. Medical Imaging: Image Processing 2007: 65123V - 2006
- [j3]Hitoshi Iyatomi, Masafumi Hagiwara:
Multipurpose image recognition based on active search and adaptive fuzzy inference neural network. Syst. Comput. Jpn. 37(3): 69-79 (2006) - [c3]Hitoshi Iyatomi, Hiroshi Oka, Masaru Tanaka, Koichi Ogawa
:
Automatic Identification of Shot Body Region from Clinical Photographies. AIPR 2006: 11 - 2005
- [c2]Hitoshi Iyatomi, Hiroshi Oka, Masahiro Hashimoto, Masaru Tanaka, Koichi Ogawa:
An Internet-based Melanoma Diagnostic System - Toward the Practical Application. CIBCB 2005: 443-446 - 2004
- [j2]Hitoshi Iyatomi, Masafumi Hagiwara:
Adaptive fuzzy inference neural network. Pattern Recognit. 37(10): 2049-2057 (2004) - 2002
- [j1]Hitoshi Iyatomi, Masafumi Hagiwara:
Scenery image recognition and interpretation using fuzzy inference neural networks. Pattern Recognit. 35(8): 1793-1806 (2002)
1990 – 1999
- 1998
- [c1]Hitoshi Iyatomi, Masafumi Hagiwara:
Knowledge extraction from scenery images and the recognition using fuzzy inference neural networks. SMC 1998: 4486-4491
Coauthor Index
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