{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,29]],"date-time":"2026-09-29T14:00:53Z","timestamp":1790690453107,"version":"4.1.0"},"publisher-location":"Cham","reference-count":20,"publisher":"Springer International Publishing","isbn-type":[{"value":"9783031160714","type":"print"},{"value":"9783031160721","type":"electronic"}],"license":[{"start":{"date-parts":[[2022,8,31]],"date-time":"2022-08-31T00:00:00Z","timestamp":1661904000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2022,8,31]],"date-time":"2022-08-31T00:00:00Z","timestamp":1661904000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2023]]},"DOI":"10.1007\/978-3-031-16072-1_9","type":"book-chapter","created":{"date-parts":[[2022,8,30]],"date-time":"2022-08-30T20:05:56Z","timestamp":1661889956000},"page":"124-135","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Siamese Neural Network for Labeling Severity of Ulcerative Colitis Video Colonoscopy: A Thick Data Approach"],"prefix":"10.1007","author":[{"given":"Jinan","family":"Fiaidhi","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sabah","family":"Mohammed","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Petros","family":"Zezos","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2022,8,31]]},"reference":[{"issue":"1","key":"9_CR1","doi-asserted-by":"publisher","first-page":"14465","DOI":"10.1038\/s41598-019-50567-5","volume":"9","author":"M Yamada","year":"2019","unstructured":"Yamada, M., et al.: Development of a real-time endoscopic image diagnosis support system using deep learning technology in colonoscopy. Sci. Rep. 9(1), 14465 (2019)","journal-title":"Sci. Rep."},{"key":"9_CR2","doi-asserted-by":"publisher","first-page":"41144","DOI":"10.1109\/ACCESS.2021.3065104","volume":"9","author":"Z Fu","year":"2021","unstructured":"Fu, Z., et al.: The future of endoscopic navigation: a review of advanced endoscopic vision technology. IEEE Access 9, 41144\u201341167 (2021)","journal-title":"IEEE Access"},{"key":"9_CR3","doi-asserted-by":"crossref","unstructured":"Xiaobei, L., et al.: Artificial intelligence\u2212 enhanced white-light colonoscopy with attention guidance predicts colorectal cancer invasion depth. Gastrointest. Endosc. 94(3), 627\u2013638.e1 (2021)","DOI":"10.1016\/j.gie.2021.03.936"},{"issue":"5","key":"9_CR4","doi-asserted-by":"publisher","first-page":"799","DOI":"10.1136\/gutjnl-2019-319914","volume":"69","author":"C Hassan","year":"2020","unstructured":"Hassan, C., et al.: New artificial intelligence system: first validation study versus experienced endoscopists for colorectal polyp detection. Gut 69(5), 799\u2013800 (2020)","journal-title":"Gut"},{"issue":"12","key":"9_CR5","doi-asserted-by":"publisher","first-page":"5666","DOI":"10.1002\/mp.13865","volume":"46","author":"X Guo","year":"2019","unstructured":"Guo, X., Zhang, N., Guo, J., Zhang, H., Hao, Y., Hang, J.: Automated polyp segmentation for colonoscopy images: a method based on convolutional neural networks and ensemble learning. Med. Phys. 46(12), 5666\u20135676 (2019)","journal-title":"Med. Phys."},{"issue":"8","key":"9_CR6","doi-asserted-by":"publisher","first-page":"e0255809","DOI":"10.1371\/journal.pone.0255809","volume":"16","author":"K Li","year":"2021","unstructured":"Li, K., et al.: Colonoscopy polyp detection and classification: dataset creation and comparative evaluations. PLOS ONE 16(8), e0255809 (2021)","journal-title":"PLOS ONE"},{"issue":"4","key":"9_CR7","doi-asserted-by":"publisher","first-page":"1069","DOI":"10.1053\/j.gastro.2018.06.037","volume":"155","author":"G Urban","year":"2018","unstructured":"Urban, G., et al.: Deep learning localizes and identifies polyps in real time with 96% accuracy in screening colonoscopy. Gastroenterology 155(4), 1069\u20131078 (2018)","journal-title":"Gastroenterology"},{"issue":"5","key":"9_CR8","doi-asserted-by":"publisher","first-page":"1593","DOI":"10.3390\/jcm9051593","volume":"9","author":"YJ Yang","year":"2020","unstructured":"Yang, Y.J., et al.: Automated classification of colorectal neoplasms in white-light colonoscopy images via deep learning. J. Clin. Med. 9(5), 1593 (2020)","journal-title":"J. Clin. Med."},{"key":"9_CR9","doi-asserted-by":"crossref","unstructured":"Medela, A., et al.: Few shot learning in histopathological images: reducing the need of labeled data on biological datasets. In: 2019 IEEE 16th International Symposium on Biomedical Imaging (ISBI 2019), pp. 1860\u20131864. IEEE (2019)","DOI":"10.1109\/ISBI.2019.8759182"},{"key":"9_CR10","unstructured":"Finn, C., Abbeel, P., Levine, S.: Model-agnostic meta-learning for fast adaptation of deep networks. In: International Conference on Machine Learning, PMLR, pp. 1126\u20131135. (2017)"},{"key":"9_CR11","doi-asserted-by":"crossref","unstructured":"Srinivasan, A., Bharadwaj, A., Sathyan, M., Natarajan, S.: Optimization of image embeddings for few shot learning. arXiv preprint arXiv:2004.02034 (2020)","DOI":"10.5220\/0010243202360242"},{"key":"9_CR12","unstructured":"Jadon, S.: An overview of deep learning architectures in few-shot learning domain. arXiv preprint arXiv:2008.06365 (2020)"},{"key":"9_CR13","doi-asserted-by":"crossref","unstructured":"Fiaidhi, J., Zezos, P., Mohammed, S.: Thick data analytics for rating ulcerative colitis severity using small endoscopy image sample. In: IEEE Big Data 2021 Conference 15\u201319 Dec 2021","DOI":"10.1109\/BigData52589.2021.9671327"},{"issue":"1","key":"9_CR14","first-page":"012029","volume":"1004","author":"J Du","year":"2018","unstructured":"Du, J.: Understanding of object detection based on CNN family and YOLO. J. Phys.: Conf. Ser. 1004(1), 012029 (2018)","journal-title":"J. Phys.: Conf. Ser."},{"issue":"1","key":"9_CR15","doi-asserted-by":"publisher","first-page":"7","DOI":"10.1159\/000518131","volume":"7","author":"AI Sharara","year":"2022","unstructured":"Sharara, A.I., Malaeb, M., Lenfant, M., Ferrante, M.: Assessment of endoscopic disease activity in ulcerative colitis: is simplicity the ultimate sophistication? Inflamm. Intest. Dis. 7(1), 7\u201312 (2022)","journal-title":"Inflamm. Intest. Dis."},{"key":"9_CR16","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"84","DOI":"10.1007\/978-3-319-24261-3_7","volume-title":"similarity-based pattern recognition","author":"E Hoffer","year":"2015","unstructured":"Hoffer, E., Ailon, N.: Deep metric learning using triplet network. In: Feragen, A., Pelillo, M., Loog, M. (eds.) SIMBAD 2015. LNCS, vol. 9370, pp. 84\u201392. Springer, Cham (2015). https:\/\/doi.org\/10.1007\/978-3-319-24261-3_7"},{"key":"9_CR17","doi-asserted-by":"crossref","unstructured":"Pogorelov, K., et al.: Kvasir: A multi-class image dataset for computer aided gastrointestinal disease detection. In: Proceedings of the 8th ACM on Multimedia Systems Conference, pp. 164\u2013169 (2017)","DOI":"10.1145\/3083187.3083212"},{"key":"9_CR18","unstructured":"Anton, M.: TrainYourOwnYOLO: Building a Custom Object Detector from Scratch, Github Repo. https:\/\/github.com\/AntonMu\/TrainYourOwnYOLO (2019)"},{"key":"9_CR19","doi-asserted-by":"crossref","unstructured":"Sawyer, D., Fiaidhi, J., Mohammed, S.: Few shot learning of covid-19 classification based on sequential and pretrained models: a thick data approach. In: 2021 IEEE 45th Annual Computers, Software, and Applications Conference (COMPSAC), pp. 1832\u20131836. IEEE (2021)","DOI":"10.1109\/COMPSAC51774.2021.00276"},{"key":"9_CR20","doi-asserted-by":"crossref","unstructured":"Heidari, M., Fouladi-Ghaleh, K.: Using Siamese Networks with Transfer Learning for Face Recognition on Small-Samples Datasets. In: 2020 International Conference on Machine Vision and Image Processing (MVIP), pp. 1\u20134. IEEE (2020)","DOI":"10.1109\/MVIP49855.2020.9116915"}],"container-title":["Lecture Notes in Networks and Systems","Intelligent Systems and Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-16072-1_9","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,8,30]],"date-time":"2022-08-30T20:14:39Z","timestamp":1661890479000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-16072-1_9"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,8,31]]},"ISBN":["9783031160714","9783031160721"],"references-count":20,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-16072-1_9","relation":{},"ISSN":["2367-3370","2367-3389"],"issn-type":[{"value":"2367-3370","type":"print"},{"value":"2367-3389","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,8,31]]},"assertion":[{"value":"31 August 2022","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"IntelliSys","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Proceedings of SAI Intelligent Systems Conference","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Amsterdam","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"The Netherlands","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2022","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"1 September 2022","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2 September 2022","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"intellisys2022","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/saiconference.com\/IntelliSys","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}