{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,10,30]],"date-time":"2024-10-30T10:27:18Z","timestamp":1730284038703,"version":"3.28.0"},"reference-count":12,"publisher":"IEEE","license":[{"start":{"date-parts":[[2020,8,1]],"date-time":"2020-08-01T00:00:00Z","timestamp":1596240000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2020,8,1]],"date-time":"2020-08-01T00:00:00Z","timestamp":1596240000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2020,8,1]],"date-time":"2020-08-01T00:00:00Z","timestamp":1596240000000},"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":[[2020,8]]},"DOI":"10.1109\/mwscas48704.2020.9184503","type":"proceedings-article","created":{"date-parts":[[2020,9,2]],"date-time":"2020-09-02T20:53:58Z","timestamp":1599080038000},"page":"391-394","source":"Crossref","is-referenced-by-count":0,"title":["Increasing CNN Representational Power Using Absolute Cosine Value Regularization"],"prefix":"10.1109","author":[{"given":"William","family":"Singleton","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Mohamed","family":"El-Sharkawy","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref4","first-page":"1603","article-title":"Diversity regularized machine","author":"yu","year":"2011","journal-title":"IJCAI"},{"key":"ref3","article-title":"Optimal brain damage","volume":"89","author":"le cun","year":"1989","journal-title":"NIPS"},{"journal-title":"9 6 0 1072779 (R2019a)","year":"2019","key":"ref10"},{"key":"ref6","article-title":"Learning multiple layers of features from tiny images","author":"krizhevsky","year":"2009","journal-title":"Tech Rep"},{"article-title":"Very deep convolutional networks for large-scale image recognition","year":"2014","author":"simonyan","key":"ref11"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-30484-3_23"},{"article-title":"Mobilenets: Efficient convolutional neural networks for mobile vision applications","year":"2017","author":"howard","key":"ref12"},{"article-title":"TensorFlow: Large-scale machine learning on heterogeneous systems","year":"2015","author":"abadi","key":"ref8"},{"article-title":"Keras","year":"2015","author":"chollet","key":"ref7"},{"article-title":"Quantizing deep convolutional networks for efficient inference: A whitepaper","year":"2018","author":"krishnamoorthi","key":"ref2"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1038\/s41592-019-0686-2"},{"article-title":"Pruning filters for efficient convnets","year":"2016","author":"li","key":"ref1"}],"event":{"name":"2020 IEEE 63rd International Midwest Symposium on Circuits and Systems (MWSCAS)","start":{"date-parts":[[2020,8,9]]},"location":"Springfield, MA, USA","end":{"date-parts":[[2020,8,12]]}},"container-title":["2020 IEEE 63rd International Midwest Symposium on Circuits and Systems (MWSCAS)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/9178719\/9184428\/09184503.pdf?arnumber=9184503","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,6,28]],"date-time":"2022-06-28T21:53:28Z","timestamp":1656453208000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9184503\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,8]]},"references-count":12,"URL":"https:\/\/doi.org\/10.1109\/mwscas48704.2020.9184503","relation":{},"subject":[],"published":{"date-parts":[[2020,8]]}}}