{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,6,19]],"date-time":"2025-06-19T05:06:30Z","timestamp":1750309590270,"version":"3.41.0"},"publisher-location":"New York, NY, USA","reference-count":15,"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\/3723178.3723279","type":"proceedings-article","created":{"date-parts":[[2025,6,6]],"date-time":"2025-06-06T07:20:33Z","timestamp":1749194433000},"page":"762-769","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["Generating Skin Lesion Hair Mask Pattern using Modified Pro-Gan"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0009-0003-3272-7079","authenticated-orcid":false,"given":"JAMILUL HUQ","family":"JAMI","sequence":"first","affiliation":[{"name":"CSE, KUET, Khulna, Bangladesh"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1869-224X","authenticated-orcid":false,"given":"Sk Imran","family":"Hossain","sequence":"additional","affiliation":[{"name":"Khulna University of Engineering &amp; Technology, Khulna, Bangladesh"}]},{"ORCID":"https:\/\/orcid.org\/0009-0005-6882-8108","authenticated-orcid":false,"given":"Abdus Salim","family":"Mollah","sequence":"additional","affiliation":[{"name":"KUET, Khulna, Bangladesh"}]}],"member":"320","published-online":{"date-parts":[[2025,6,6]]},"reference":[{"key":"e_1_3_3_1_2_2","doi-asserted-by":"crossref","unstructured":"Zafar K. Gilani S.O. Waris A. Ahmed A. Jamil M. Khan M.N. & Sohail Kashif A. (2020). Skin Lesion Segmentation from Dermoscopic Images Using Convolutional Neural Network. Sensors 20 1601.","DOI":"10.3390\/s20061601"},{"key":"e_1_3_3_1_3_2","doi-asserted-by":"crossref","unstructured":"Siddique N. Paheding S. Elkin C. P. & Devabhaktuni V. (2021). U-Net and Its Variants for Medical Image Segmentation: A Review of Theory and Applications. *IEEE Access* 9 82031-82057. doi: 10.1109\/ACCESS.2021.3086020.","DOI":"10.1109\/ACCESS.2021.3086020"},{"key":"e_1_3_3_1_4_2","doi-asserted-by":"crossref","unstructured":"Yoon H.-S.; Park S.-W.; Yoo J.-H. \"Real-Time Hair Segmentation Using Mobile-Unet \" Electronics vol. 10 p. 99 2021.","DOI":"10.3390\/electronics10020099"},{"key":"e_1_3_3_1_5_2","doi-asserted-by":"crossref","unstructured":"Lama N. Kasmi R. Hagerty J.R. et al. \"ChimeraNet: U-Net for Hair Detection in Dermoscopic Skin Lesion Images.\" *J Digit Imaging* 36 526\u2013535 (2023). doi: 10.1007\/s10278-022-00740-6.","DOI":"10.1007\/s10278-022-00740-6"},{"key":"e_1_3_3_1_6_2","doi-asserted-by":"crossref","unstructured":"M. Attia et al. \"Realistic hair simulator for skin lesion images: A novel benchmarking tool \" *Artificial Intelligence in Medicine* vol. 108 p. 101933 2020.","DOI":"10.1016\/j.artmed.2020.101933"},{"key":"e_1_3_3_1_7_2","doi-asserted-by":"crossref","unstructured":"B. Liu et al. \"Application of an improved DCGAN for image generation \" *Mobile Information Systems* vol. 2022 2022.","DOI":"10.1155\/2022\/9005552"},{"key":"e_1_3_3_1_8_2","doi-asserted-by":"crossref","unstructured":"Richardson E. Alaluf Y. Patashnik O. Nitzan Y. Azar Y. Shapiro S. & Cohen-Or D. (2021). Encoding in Style: A StyleGAN Encoder for Image-to-Image Translation. In *Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR)* (pp. 2287-2296). June 2021.","DOI":"10.1109\/CVPR46437.2021.00232"},{"key":"e_1_3_3_1_9_2","doi-asserted-by":"crossref","unstructured":"H. Gao J. Pei and H. Huang \"ProGAN: Network Embedding via Proximity Generative Adversarial Network \" in *Proceedings of the Association for Computing Machinery* (2019) New York NY USA pp. 1-6. doi: 10.1145\/3292500.3330866.","DOI":"10.1145\/3292500.3330866"},{"key":"e_1_3_3_1_10_2","unstructured":"R. Ronneberger P. Fischer and T. Brox \"U-net: Convolutional networks for biomedical image segmentation \" in *Medical image computing and computer-assisted intervention\u2013MICCAI 2015: 18th international conference* Munich Germany October 5-9 2015 proceedings part III vol. 18. Springer International Publishing 2015."},{"key":"e_1_3_3_1_11_2","doi-asserted-by":"crossref","unstructured":"Hossain Sk Imran et al. \"A skin lesion hair mask dataset with fine-grained annotations.\" Data in Brief vol. 48 2023 p. 109249.","DOI":"10.1016\/j.dib.2023.109249"},{"key":"e_1_3_3_1_12_2","unstructured":"Ndajah Peter et al. \"SSIM image quality metric for denoised images.\" Proc. 3rd WSEAS Int. Conf. on Visualization Imaging and Simulation. 2010."},{"key":"e_1_3_3_1_13_2","doi-asserted-by":"crossref","unstructured":"Walid El-Shafai Ibrahim Abd El-Fattah and Taha E. Taha. 2023. Deep learning-based hair removal for improved diagnostics of skin diseases. Multimedia Tools and Applications 1\u201325.","DOI":"10.1007\/s11042-023-16646-6"},{"key":"e_1_3_3_1_14_2","doi-asserted-by":"crossref","unstructured":"Xiaoxuan Liu et al. 2019. A comparison of deep learning performance against health-care professionals in detecting diseases from medical imaging: a systematic review and meta-analysis. The Lancet Digital Health 1 6 (2019) e271\u2013e297.","DOI":"10.1016\/S2589-7500(19)30123-2"},{"key":"e_1_3_3_1_15_2","doi-asserted-by":"crossref","unstructured":"Nafiseh Ghaffar Nia Erkan Kaplanoglu and Ahad Nasab. 2023. Evaluation of artificial intelligence techniques in disease diagnosis and prediction. Discover Artificial Intelligence 3 1 (2023) 5.","DOI":"10.1007\/s44163-023-00049-5"},{"key":"e_1_3_3_1_16_2","unstructured":"Gulrajani I. Ahmed F. Arjovsky M. Dumoulin V. & Courville A. (2017). Improved Training of Wasserstein GANs. In *Proceedings of the 31st International Conference on Neural Information Processing Systems* (pp. 5769-5779)."}],"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\/3723178.3723279","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3723178.3723279","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\/3723178.3723279"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,10,17]]},"references-count":15,"alternative-id":["10.1145\/3723178.3723279","10.1145\/3723178"],"URL":"https:\/\/doi.org\/10.1145\/3723178.3723279","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"}}]}}