{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,16]],"date-time":"2026-07-16T14:58:39Z","timestamp":1784213919512,"version":"3.55.0"},"reference-count":62,"publisher":"MDPI AG","issue":"1","license":[{"start":{"date-parts":[[2022,12,21]],"date-time":"2022-12-21T00:00:00Z","timestamp":1671580800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"National Key Research and Development Program of China","award":["2017YFA0700300"],"award-info":[{"award-number":["2017YFA0700300"]}]},{"name":"National Key Research and Development Program of China","award":["61903356"],"award-info":[{"award-number":["61903356"]}]},{"name":"National Key Research and Development Program of China","award":["2021-MS-030"],"award-info":[{"award-number":["2021-MS-030"]}]},{"name":"National Key Research and Development Program of China","award":["2022JH6\/100100013"],"award-info":[{"award-number":["2022JH6\/100100013"]}]},{"name":"National Key Research and Development Program of China","award":["2022-Z03"],"award-info":[{"award-number":["2022-Z03"]}]},{"name":"National Natural Science Foundation of China","award":["2017YFA0700300"],"award-info":[{"award-number":["2017YFA0700300"]}]},{"name":"National Natural Science Foundation of China","award":["61903356"],"award-info":[{"award-number":["61903356"]}]},{"name":"National Natural Science Foundation of China","award":["2021-MS-030"],"award-info":[{"award-number":["2021-MS-030"]}]},{"name":"National Natural Science Foundation of China","award":["2022JH6\/100100013"],"award-info":[{"award-number":["2022JH6\/100100013"]}]},{"name":"National Natural Science Foundation of China","award":["2022-Z03"],"award-info":[{"award-number":["2022-Z03"]}]},{"name":"Liaoning Natural Science Foundation","award":["2017YFA0700300"],"award-info":[{"award-number":["2017YFA0700300"]}]},{"name":"Liaoning Natural Science Foundation","award":["61903356"],"award-info":[{"award-number":["61903356"]}]},{"name":"Liaoning Natural Science Foundation","award":["2021-MS-030"],"award-info":[{"award-number":["2021-MS-030"]}]},{"name":"Liaoning Natural Science Foundation","award":["2022JH6\/100100013"],"award-info":[{"award-number":["2022JH6\/100100013"]}]},{"name":"Liaoning Natural Science Foundation","award":["2022-Z03"],"award-info":[{"award-number":["2022-Z03"]}]},{"name":"Independent project of State Key Laboratory of Robotics","award":["2017YFA0700300"],"award-info":[{"award-number":["2017YFA0700300"]}]},{"name":"Independent project of State Key Laboratory of Robotics","award":["61903356"],"award-info":[{"award-number":["61903356"]}]},{"name":"Independent project of State Key Laboratory of Robotics","award":["2021-MS-030"],"award-info":[{"award-number":["2021-MS-030"]}]},{"name":"Independent project of State Key Laboratory of Robotics","award":["2022JH6\/100100013"],"award-info":[{"award-number":["2022JH6\/100100013"]}]},{"name":"Independent project of State Key Laboratory of Robotics","award":["2022-Z03"],"award-info":[{"award-number":["2022-Z03"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Entropy"],"abstract":"<jats:p>The increasingly large structure of neural networks makes it difficult to deploy on edge devices with limited computing resources. Network pruning has become one of the most successful model compression methods in recent years. Existing works typically compress models based on importance, removing unimportant filters. This paper reconsiders model pruning from the perspective of structural redundancy, claiming that identifying functionally similar filters plays a more important role, and proposes a model pruning framework for clustering-based redundancy identification. First, we perform cluster analysis on the filters of each layer to generate similar sets with different functions. We then propose a criterion for identifying redundant filters within similar sets. Finally, we propose a pruning scheme that automatically determines the pruning rate of each layer. Extensive experiments on various benchmark network architectures and datasets demonstrate the effectiveness of our proposed framework.<\/jats:p>","DOI":"10.3390\/e25010009","type":"journal-article","created":{"date-parts":[[2022,12,22]],"date-time":"2022-12-22T02:59:06Z","timestamp":1671677946000},"page":"9","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Cluster-Based Structural Redundancy Identification for Neural Network Compression"],"prefix":"10.3390","volume":"25","author":[{"given":"Tingting","family":"Wu","sequence":"first","affiliation":[{"name":"State Key Laboratory of Robotics, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 110016, China"},{"name":"Key Laboratory of Networked Control Systems, Chinese Academy of Sciences, Shenyang 110016, China"},{"name":"Institutes for Robotics and Intelligent Manufacturing, Chinese Academy of Sciences, Shenyang 110169, China"},{"name":"University of Chinese Academy of Sciences, Beijing 100049, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8392-1777","authenticated-orcid":false,"given":"Chunhe","family":"Song","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Robotics, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 110016, China"},{"name":"Key Laboratory of Networked Control Systems, Chinese Academy of Sciences, Shenyang 110016, China"},{"name":"Institutes for Robotics and Intelligent Manufacturing, Chinese Academy of Sciences, Shenyang 110169, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Peng","family":"Zeng","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Robotics, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 110016, China"},{"name":"Key Laboratory of Networked Control Systems, Chinese Academy of Sciences, Shenyang 110016, China"},{"name":"Institutes for Robotics and Intelligent Manufacturing, Chinese Academy of Sciences, Shenyang 110169, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Changqing","family":"Xia","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Robotics, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 110016, China"},{"name":"Key Laboratory of Networked Control Systems, Chinese Academy of Sciences, Shenyang 110016, China"},{"name":"Institutes for Robotics and Intelligent Manufacturing, Chinese Academy of Sciences, Shenyang 110169, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2022,12,21]]},"reference":[{"key":"ref_1","unstructured":"Krizhevsky, A., Sutskever, I., and Hinton, G.E. 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