{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,24]],"date-time":"2026-01-24T17:34:41Z","timestamp":1769276081383,"version":"3.49.0"},"reference-count":25,"publisher":"IEEE","license":[{"start":{"date-parts":[[2022,6,19]],"date-time":"2022-06-19T00:00:00Z","timestamp":1655596800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2022,6,19]],"date-time":"2022-06-19T00:00:00Z","timestamp":1655596800000},"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":[[2022,6,19]]},"DOI":"10.1109\/newcas52662.2022.9842117","type":"proceedings-article","created":{"date-parts":[[2022,8,5]],"date-time":"2022-08-05T19:33:34Z","timestamp":1659728014000},"page":"402-406","source":"Crossref","is-referenced-by-count":4,"title":["Clustered Network Adaptation Methodology for the Resource Constrained Platform"],"prefix":"10.1109","author":[{"given":"Pratibha","family":"Verma","sequence":"first","affiliation":[{"name":"Indian Institute of Technology,Department of Electrical Engineering,Hyderabad,India"}]},{"given":"Pradip","family":"Sasmal","sequence":"additional","affiliation":[{"name":"Indian Institute of Technology,Department of Electrical Engineering,Hyderabad,India"}]},{"given":"Chandrajit","family":"Pal","sequence":"additional","affiliation":[{"name":"Indian Institute of Technology,Department of Electrical Engineering,Hyderabad,India"}]},{"given":"Sumohana","family":"Channappayya","sequence":"additional","affiliation":[{"name":"Indian Institute of Technology,Department of Electrical Engineering,Hyderabad,India"}]},{"given":"Amit","family":"Acharyya","sequence":"additional","affiliation":[{"name":"Indian Institute of Technology,Department of Electrical Engineering,Hyderabad,India"}]}],"member":"263","reference":[{"key":"ref10","article-title":"Predicting parameters in deep learning","volume":"26","author":"denil","year":"2013","journal-title":"Advances in neural information processing systems"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2015.7298594"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/ICASSP.2015.7178146"},{"key":"ref13","article-title":"Compressing neural networks with the hashing trick","author":"chen","year":"2015","journal-title":"International Conference on Machine Learning"},{"key":"ref14","article-title":"Compressing deep convolutional networks using vector quantization","author":"gong","year":"2014"},{"key":"ref15","article-title":"Efficient processing of deep neural networks: A tutorial and survey. arXiv 2017","author":"sze","year":"2017"},{"key":"ref16","article-title":"Learning both weights and connections for efficient neural network","volume":"28","author":"han","year":"2015","journal-title":"Advances in neural information processing systems"},{"key":"ref17","article-title":"Optimal brain damage","volume":"2","author":"lecun","year":"1989","journal-title":"Advances in neural information processing systems"},{"key":"ref18","article-title":"Pruning convolutional neural networks for resource efficient inference","author":"molchanov","year":"2016"},{"key":"ref19","article-title":"Network trimming: A data-driven neuron pruning approach towards efficient deep architectures","author":"hu","year":"2016"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1016\/j.neunet.2005.06.042"},{"key":"ref3","article-title":"Neural turing machines","author":"graves","year":"2014"},{"key":"ref6","article-title":"Deep compression: Compressing deep neural networks with pruning, trained quantization and huffman coding","author":"han","year":"2015"},{"key":"ref5","first-page":"2493","article-title":"Natural language processing (almost) from scratch","author":"collobert","year":"2011","journal-title":"Journal of machine learning research 12 ARTICLE"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-01249-6_18"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1007\/s00034-020-01534-3"},{"key":"ref2","article-title":"Very deep convolutional networks for large-scale image recognition","author":"simonyan","year":"2014"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2020.acl-main.686"},{"key":"ref1","article-title":"Imagenet classification with deep convolutional neural networks","volume":"25","author":"krizhevsky","year":"2012","journal-title":"Advances in neural information processing systems"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.5244\/C.29.31"},{"key":"ref22","article-title":"Adc: Automated deep compression and acceleration with reinforcement learning","author":"he","year":"2018"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00171"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1109\/ACSSC.2017.8335698"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.643"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1109\/JSSC.2016.2616357"}],"event":{"name":"2022 20th IEEE Interregional NEWCAS Conference (NEWCAS)","location":"Quebec City, QC, Canada","start":{"date-parts":[[2022,6,19]]},"end":{"date-parts":[[2022,6,22]]}},"container-title":["2022 20th IEEE Interregional NEWCAS Conference (NEWCAS)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/9841660\/9841947\/09842117.pdf?arnumber=9842117","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,8,16]],"date-time":"2022-08-16T03:05:22Z","timestamp":1660619122000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9842117\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,6,19]]},"references-count":25,"URL":"https:\/\/doi.org\/10.1109\/newcas52662.2022.9842117","relation":{},"subject":[],"published":{"date-parts":[[2022,6,19]]}}}