Chadebecq F, Lovat LB, Stoyanov D (2023) Artificial intelligence and automation in endoscopy and surgery. Nat Rev Gastroenterol Hepatol 20(3):171–182
He Q, Bano S, Ahmad OF, Yang B, Chen X, Valdastri P, Lovat LB, Stoyanov D, Zuo S (2020) Deep learning-based anatomical site classification for upper gastrointestinal endoscopy. Int J Comput Assist Radiol Surg 15:1085–1094
Article PubMed PubMed Central Google Scholar
Du R, Chang D, Bhunia AK, Xie J, Ma Z, Song Y-Z, Guo J (2020) Fine-grained visual classification via progressive multi-granularity training of jigsaw patches. In: European Conference on Computer Vision, p 153–168
Chang D, Pang K, Zheng Y, Ma Z, Song Y-Z, Guo J (2021) Your “flamingo” is my “bird”: fine-grained, or not. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, p 11476–11485
Zhang L, Huang S, Liu W, Tao D (2019) Learning a mixture of granularity-specific experts for fine-grained categorization. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, p 8331–8340
Zheng H, Fu J, Mei T, Luo J (2017) Learning multi-attention convolutional neural network for fine-grained image recognition. In: Proceedings of the IEEE International Conference on Computer Vision, p 5209–5217
Yang Z, Luo T, Wang D, Hu Z, Gao J, Wang L (2018) Learning to navigate for fine-grained classification. In: Proceedings of the European Conference on Computer Vision, p 420–435
Borgli H, Thambawita V, Smedsrud PH, Hicks S, Jha D, Eskeland SL, Randel KR, Pogorelov K, Lux M, Nguyen DTD et al (2020) Hyperkvasir, a comprehensive multi-class image and video dataset for gastrointestinal endoscopy. Sci Data 7(1):283
Article PubMed PubMed Central Google Scholar
Hicks SA, Jha D, Thambawita V, Halvorsen P, Hammer HL, Riegler MA (2021) The endotect 2020 challenge: evaluation and comparison of classification, segmentation and inference time for endoscopy. In: Pattern Recognition. ICPR International Workshops and Challenges, p 263–274
Jha D, Sharma V, Dasu N, Tomar NK, Hicks S, Bhuyan M, Das PK, Riegler MA, Halvorsen P, Bagci U, et al (2023) Gastrovision: A multi-class endoscopy image dataset for computer aided gastrointestinal disease detection. In: Workshop on Machine Learning for Multimodal Healthcare Data, p 125–140
Dutta A, Bhattacharjee RK, Barbhuiya FA (2021) Efficient detection of lesions during endoscopy. In: Pattern Recognition. ICPR International Workshops and Challenges, p 315–322
Khan Z, Alvi MUT, Tahir MA, Memon S (2021) Medical diagnostic by data bagging for various instances of neural network. In: Pattern Recognition. ICPR International Workshops and Challenges, p 291–298
Luo Z, Che L, He J (2021) Delving into high quality endoscopic diagnoses. In: Pattern Recognition. ICPR International Workshops and Challenges, p 283–290
Galdran A, Carneiro G, Ballester MAG (2021) A hierarchical multi-task approach to gastrointestinal image analysis. In: Pattern Recognition. ICPR International Workshops and Challenges, p 275–282
He Q, Bano S, Stoyanov D, Zuo S (2021) Hybrid loss with network trimming for disease recognition in gastrointestinal endoscopy. In: Pattern Recognition. ICPR International Workshops and Challenges, p 299–306
Galdran A, Carneiro G, González Ballester MA (2021) Balanced-mixup for highly imbalanced medical image classification. In: Medical Image Computing and Computer Assisted Intervention, p 323–333
Li J, Chen G, Mao H, Deng D, Li D, Hao J, Dou Q, Heng P-A (2022) Flat-aware cross-stage distilled framework for imbalanced medical image classification. In: International Conference on Medical Image Computing and Computer-Assisted Intervention, p 217–226
Kolesnikov A, Beyer L, Zhai X, Puigcerver J, Yung J, Gelly S, Houlsby N (2020) Big transfer (bit): General visual representation learning. In: European Conference on Computer Vision, p 491–507
Selvaraju RR, Cogswell M, Das A, Vedantam R, Parikh D, Batra D (2020) Grad-cam: visual explanations from deep networks via gradient-based localization. Int J Comput Vision 128:336–359
Comments (0)