{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,25]],"date-time":"2026-02-25T08:23:50Z","timestamp":1772007830511,"version":"3.50.1"},"reference-count":25,"publisher":"IEEE","license":[{"start":{"date-parts":[[2025,12,1]],"date-time":"2025-12-01T00:00:00Z","timestamp":1764547200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2025,12,1]],"date-time":"2025-12-01T00:00:00Z","timestamp":1764547200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2025,12,1]]},"DOI":"10.1109\/vcip67698.2025.11396887","type":"proceedings-article","created":{"date-parts":[[2026,2,24]],"date-time":"2026-02-24T20:55:27Z","timestamp":1771966527000},"page":"1-5","source":"Crossref","is-referenced-by-count":0,"title":["Stop-band Energy Constraint for Orthogonal Tunable Wavelet Units in Convolutional Neural Networks for Computer Vision problems"],"prefix":"10.1109","author":[{"given":"An D.","family":"Le","sequence":"first","affiliation":[{"name":"University of California San Diego,Jacobs School of Engineering,La Jolla,CA,USA,92093"}]},{"given":"Hung","family":"Nguyen","sequence":"additional","affiliation":[{"name":"University of California San Diego,Jacobs School of Engineering,La Jolla,CA,USA,92093"}]},{"given":"Sungbal","family":"Seo","sequence":"additional","affiliation":[{"name":"Tech University of Korea,Department of Computer Engineering,Siheung,South Korea,15073"}]},{"given":"You-Suk","family":"Bae","sequence":"additional","affiliation":[{"name":"Tech University of Korea,Department of Computer Engineering,Siheung,South Korea,15073"}]},{"given":"Truong Q.","family":"Nguyen","sequence":"additional","affiliation":[{"name":"University of California San Diego,Jacobs School of Engineering,La Jolla,CA,USA,92093"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-73119-8_4"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1097\/iae.0000000000004606"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.47852\/bonviewJCCE42023264"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-47454-5_8"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/RIVF55975.2022.10013864"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.90"},{"key":"ref7","article-title":"Making convolutional networks shift-invariant again","author":"Zhang","year":"2019","journal-title":"ICML"},{"key":"ref8","first-page":"2449","article-title":"Spectral representations for convolutional neural networks","volume-title":"Proceedings of the 28th International Conference on Neural Information Processing Systems - Volume 2, NIPS\u201915","author":"Rippel"},{"key":"ref9","article-title":"Learning strides in convolutional neural networks","author":"Riad","year":"2022","journal-title":"ICLR"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00727"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1007\/s00530-022-00889-8"},{"key":"ref12","article-title":"Learning multiple layers of features from tiny images","author":"Krizhevsky","year":"2009"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00982"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1007\/s11263-020-01400-4"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2014.461"},{"key":"ref16","first-page":"OD98","article-title":"Using artificial intelligence to predict visual function from retinal structure in retinitis pigmentosa","volume":"66","author":"Yassin","year":"2025","journal-title":"Investigative Ophthalmology & Visual Science"},{"key":"ref17","first-page":"2256","article-title":"Ai versus human analysis for detecting ilm removal in erm surgery based on post-operative oct","volume":"66","author":"MEHTA","year":"2025","journal-title":"Investigative Ophthalmology & Visual Science"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2024.3418752"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/OJSP.2025.3580967"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1109\/WACV51458.2022.00188"},{"key":"ref21","first-page":"111","article-title":"A theoretical analysis of feature pooling in visual recognition","volume-title":"Proceedings of the 27th International Conference on International Conference on Machine Learning, ICML\u201910","author":"Boureau"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/IJCNN.1992.287150"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1109\/34.192463"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1093\/oso\/9780195094237.003.0002"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1109\/VCIP59821.2023.10402772"}],"event":{"name":"2025 International Conference on Visual Communications and Image Processing (VCIP)","location":"Klagenfurt, Austria","start":{"date-parts":[[2025,12,1]]},"end":{"date-parts":[[2025,12,4]]}},"container-title":["2025 International Conference on Visual Communications and Image Processing (VCIP)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx8\/11396756\/11396790\/11396887.pdf?arnumber=11396887","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,2,25]],"date-time":"2026-02-25T07:43:45Z","timestamp":1772005425000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/11396887\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,12,1]]},"references-count":25,"URL":"https:\/\/doi.org\/10.1109\/vcip67698.2025.11396887","relation":{},"subject":[],"published":{"date-parts":[[2025,12,1]]}}}