{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,6,19]],"date-time":"2025-06-19T05:06:29Z","timestamp":1750309589629,"version":"3.41.0"},"publisher-location":"New York, NY, USA","reference-count":21,"publisher":"ACM","license":[{"start":{"date-parts":[[2024,10,17]],"date-time":"2024-10-17T00:00:00Z","timestamp":1729123200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2024,10,17]]},"DOI":"10.1145\/3723178.3723297","type":"proceedings-article","created":{"date-parts":[[2025,6,6]],"date-time":"2025-06-06T07:16:47Z","timestamp":1749194207000},"page":"896-901","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["AI-assisted polyps detection to facilitate autonomous endoscopy examination"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0009-0009-8708-6364","authenticated-orcid":false,"given":"Munim","family":"Ahmed","sequence":"first","affiliation":[{"name":"American International University Bangladesh, Dhaka, Bangladesh"}]},{"ORCID":"https:\/\/orcid.org\/0009-0005-1615-1617","authenticated-orcid":false,"given":"Md Sahilur","family":"Rahman","sequence":"additional","affiliation":[{"name":"American International University-Bangladesh, Dhaka, Bangladesh"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0713-0740","authenticated-orcid":false,"given":"Md Shakhawat","family":"Hossain","sequence":"additional","affiliation":[{"name":"Independent University Bangladesh, Dhaka, Bangladesh"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9391-2863","authenticated-orcid":false,"given":"Mahmudur","family":"Rahman","sequence":"additional","affiliation":[{"name":"American International University-Bangladesh, Dhaka, Bangladesh"}]},{"ORCID":"https:\/\/orcid.org\/0009-0005-9093-2294","authenticated-orcid":false,"given":"Fariha","family":"Karim","sequence":"additional","affiliation":[{"name":"American International University-Bangladesh, Dhaka, Bangladesh"}]},{"ORCID":"https:\/\/orcid.org\/0009-0000-9470-5308","authenticated-orcid":false,"given":"Mahreen","family":"Tabassum","sequence":"additional","affiliation":[{"name":"American International University-Bangladesh, Dhaka, Bangladesh"}]}],"member":"320","published-online":{"date-parts":[[2025,6,6]]},"reference":[{"key":"e_1_3_3_1_2_2","doi-asserted-by":"crossref","unstructured":"Heba\u00a0M Afify Kamel\u00a0K Mohammed and Aboul\u00a0Ella Hassanien. 2021. An improved framework for polyp image segmentation based on SegNet architecture. International Journal of Imaging Systems and Technology 31 3 (2021) 1741\u20131751.","DOI":"10.1002\/ima.22568"},{"key":"e_1_3_3_1_3_2","doi-asserted-by":"crossref","unstructured":"Ishita Barua Daniela\u00a0Guerrero Vinsard Henriette\u00a0C Jodal Magnus L\u00f8berg Mette Kalager \u00d8yvind Holme Masashi Misawa Michael Bretthauer and Yuichi Mori. 2021. Artificial intelligence for polyp detection during colonoscopy: a systematic review and meta-analysis. Endoscopy 53 03 (2021) 277\u2013284.","DOI":"10.1055\/a-1201-7165"},{"key":"e_1_3_3_1_4_2","doi-asserted-by":"crossref","unstructured":"Jorge Bernal Javier S\u00e1nchez and Fernando Vilarino. 2012. Towards automatic polyp detection with a polyp appearance model. Pattern Recognition 45 9 (2012) 3166\u20133182.","DOI":"10.1016\/j.patcog.2012.03.002"},{"key":"e_1_3_3_1_5_2","doi-asserted-by":"crossref","unstructured":"Hanna Borgli Vajira Thambawita Pia\u00a0H Smedsrud Steven Hicks Debesh Jha Sigrun\u00a0L Eskeland Kristin\u00a0Ranheim Randel Konstantin Pogorelov Mathias Lux Duc Tien\u00a0Dang Nguyen et\u00a0al. 2020. HyperKvasir a comprehensive multi-class image and video dataset for gastrointestinal endoscopy. Scientific data 7 1 (2020) 283.","DOI":"10.1038\/s41597-020-00622-y"},{"key":"e_1_3_3_1_6_2","doi-asserted-by":"crossref","unstructured":"Shweta Gangrade Prakash\u00a0Chandra Sharma and Akhilesh\u00a0Kumar Sharma. 2023. Computer-Aided Polyps Classification from Colonoscopy Using Stacking-Based Deep Learning Model. Authorea Preprints (2023).","DOI":"10.22541\/au.169650914.47795628\/v1"},{"key":"e_1_3_3_1_7_2","doi-asserted-by":"crossref","unstructured":"Yunbo Guo Jorge Bernal and Bogdan J.\u00a0Matuszewski. 2020. Polyp segmentation with fully convolutional deep neural networks\u2014extended evaluation study. Journal of Imaging 6 7 (2020) 69.","DOI":"10.3390\/jimaging6070069"},{"key":"e_1_3_3_1_8_2","doi-asserted-by":"crossref","unstructured":"Md\u00a0Shakhawat Hossain Md\u00a0Mahmudur Rahman MM\u00a0Mahbubul Syeed Mohammad\u00a0Faisal Uddin Mahady Hasan Md\u00a0Aulad Hossain Amel Ksibi Mona\u00a0M Jamjoom Zahid Ullah and Md\u00a0Abdus Samad. 2023. Deeppoly: deep learning based polyps segmentation and classification for autonomous colonoscopy examination. IEEE Access (2023).","DOI":"10.1109\/ACCESS.2023.3310541"},{"key":"e_1_3_3_1_9_2","doi-asserted-by":"crossref","unstructured":"Md\u00a0Shakhawat Hossain Md\u00a0Sahilur Rahman Munim Ahmed Nazia Alfaz Sirajum\u00a0Munira Shifat MM\u00a0Mahbubul Syeed Mohammad\u00a0Anowar Hussen and Mohammad\u00a0Faisal Uddin. 2024. Residual Tumor Cellularity Assessment of Breast Cancer after Neoadjuvant Therapy using Image Transformer. IEEE Access (2024).","DOI":"10.1109\/ACCESS.2024.3415665"},{"key":"e_1_3_3_1_10_2","doi-asserted-by":"crossref","unstructured":"Debesh Jha Sharib Ali Nikhil\u00a0Kumar Tomar H\u00e5vard\u00a0D Johansen Dag Johansen Jens Rittscher Michael\u00a0A Riegler and P\u00e5l Halvorsen. 2021. Real-time polyp detection localization and segmentation in colonoscopy using deep learning. Ieee Access 9 (2021) 40496\u201340510.","DOI":"10.1109\/ACCESS.2021.3063716"},{"key":"e_1_3_3_1_11_2","doi-asserted-by":"crossref","unstructured":"Debesh Jha Pia\u00a0H Smedsrud Dag Johansen Thomas De\u00a0Lange H\u00e5vard\u00a0D Johansen P\u00e5l Halvorsen and Michael\u00a0A Riegler. 2021. A comprehensive study on colorectal polyp segmentation with ResUNet++ conditional random field and test-time augmentation. IEEE journal of biomedical and health informatics 25 6 (2021) 2029\u20132040.","DOI":"10.1109\/JBHI.2021.3049304"},{"key":"e_1_3_3_1_12_2","doi-asserted-by":"crossref","unstructured":"Young\u00a0Jae Kim Jang\u00a0Pyo Bae Jun-Won Chung Dong\u00a0Kyun Park Kwang\u00a0Gi Kim and Yoon\u00a0Jae Kim. 2021. New polyp image classification technique using transfer learning of network-in-network structure in endoscopic images. Scientific Reports 11 1 (2021) 3605.","DOI":"10.1038\/s41598-021-83199-9"},{"key":"e_1_3_3_1_13_2","doi-asserted-by":"publisher","DOI":"10.1109\/CISP-BMEI.2017.8301980"},{"key":"e_1_3_3_1_14_2","doi-asserted-by":"crossref","unstructured":"Win\u00a0Sheng Liew Tong\u00a0Boon Tang Cheng-Hung Lin and Cheng-Kai Lu. 2021. Automatic colonic polyp detection using integration of modified deep residual convolutional neural network and ensemble learning approaches. Computer Methods and Programs in Biomedicine 206 (2021) 106114.","DOI":"10.1016\/j.cmpb.2021.106114"},{"key":"e_1_3_3_1_15_2","doi-asserted-by":"crossref","unstructured":"Subhashree Mohapatra Girish\u00a0Kumar Pati Manohar Mishra and Tripti Swarnkar. 2022. Upolyseg: A u-net-based polyp segmentation network using colonoscopy images. Gastroenterology Insights 13 3 (2022) 264\u2013274.","DOI":"10.3390\/gastroent13030027"},{"key":"e_1_3_3_1_16_2","doi-asserted-by":"crossref","unstructured":"Muhammad Ramzan Mudassar Raza Muhammad\u00a0Imran Sharif and Seifedine Kadry. 2022. Gastrointestinal tract polyp anomaly segmentation on colonoscopy images using graft-U-Net. Journal of Personalized Medicine 12 9 (2022) 1459.","DOI":"10.3390\/jpm12091459"},{"key":"e_1_3_3_1_17_2","doi-asserted-by":"crossref","unstructured":"Sirojbek Safarov and Taeg\u00a0Keun Whangbo. 2021. A-DenseUNet: Adaptive densely connected UNet for polyp segmentation in colonoscopy images with atrous convolution. Sensors 21 4 (2021) 1441.","DOI":"10.3390\/s21041441"},{"key":"e_1_3_3_1_18_2","doi-asserted-by":"crossref","unstructured":"Younghak Shin and Ilangko Balasingham. 2018. Automatic polyp frame screening using patch based combined feature and dictionary learning. Computerized Medical Imaging and Graphics 69 (2018) 33\u201342.","DOI":"10.1016\/j.compmedimag.2018.08.001"},{"key":"e_1_3_3_1_19_2","first-page":"10347","volume-title":"International conference on machine learning","author":"Touvron Hugo","year":"2021","unstructured":"Hugo Touvron, Matthieu Cord, Matthijs Douze, Francisco Massa, Alexandre Sablayrolles, and Herv\u00e9 J\u00e9gou. 2021. Training data-efficient image transformers & distillation through attention. In International conference on machine learning. PMLR, 10347\u201310357."},{"key":"e_1_3_3_1_20_2","doi-asserted-by":"crossref","unstructured":"Kun Yang Shilong Chang Zhaoxing Tian Cong Gao Yu Du Xiongfeng Zhang Kun Liu Jie Meng and Linyan Xue. 2022. Automatic polyp detection and segmentation using shuffle efficient channel attention network. Alexandria Engineering Journal 61 1 (2022) 917\u2013926.","DOI":"10.1016\/j.aej.2021.04.072"},{"key":"e_1_3_3_1_21_2","doi-asserted-by":"crossref","unstructured":"Yao Yao Shuiping Gou Ru Tian Xiangrong Zhang Shuixiang He et\u00a0al. 2021. Automated classification and segmentation in colorectal images based on self-paced transfer network. BioMed Research International 2021 (2021).","DOI":"10.1155\/2021\/6683931"},{"key":"e_1_3_3_1_22_2","doi-asserted-by":"crossref","unstructured":"Farah Younas Muhammad Usman and Wei\u00a0Qi Yan. 2023. A deep ensemble learning method for colorectal polyp classification with optimized network parameters. Applied Intelligence 53 2 (2023) 2410\u20132433.","DOI":"10.1007\/s10489-022-03689-9"}],"event":{"name":"ICCA 2024: 3rd International Conference on Computing Advancements","acronym":"ICCA 2024","location":"Dhaka Bangladesh"},"container-title":["Proceedings of the 3rd International Conference on Computing Advancements"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3723178.3723297","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3723178.3723297","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,19]],"date-time":"2025-06-19T01:56:47Z","timestamp":1750298207000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3723178.3723297"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,10,17]]},"references-count":21,"alternative-id":["10.1145\/3723178.3723297","10.1145\/3723178"],"URL":"https:\/\/doi.org\/10.1145\/3723178.3723297","relation":{},"subject":[],"published":{"date-parts":[[2024,10,17]]},"assertion":[{"value":"2025-06-06","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}