{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,28]],"date-time":"2026-03-28T06:30:39Z","timestamp":1774679439958,"version":"3.50.1"},"reference-count":80,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"9","license":[{"start":{"date-parts":[[2022,9,1]],"date-time":"2022-09-01T00:00:00Z","timestamp":1661990400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2022,9,1]],"date-time":"2022-09-01T00:00:00Z","timestamp":1661990400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2022,9,1]],"date-time":"2022-09-01T00:00:00Z","timestamp":1661990400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"name":"Research Foundation Capacity Improvement Project for Young and Middle-Aged Teachers in Guangxi Universities of China in 2020","award":["2020KY02029"],"award-info":[{"award-number":["2020KY02029"]}]},{"DOI":"10.13039\/501100009007","name":"Education and Teaching Reform Project of Guangxi Normal University in 2019","doi-asserted-by":"publisher","award":["2019JGB36"],"award-info":[{"award-number":["2019JGB36"]}],"id":[{"id":"10.13039\/501100009007","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Guangxi Vocational Education Teaching Reform Research Project in 2020","award":["GXGZJG2020B101"],"award-info":[{"award-number":["GXGZJG2020B101"]}]},{"DOI":"10.13039\/501100004054","name":"The Deanship of Scientific Research (DSR) at King Abdulaziz University","doi-asserted-by":"publisher","award":["RG-6-135-38"],"award-info":[{"award-number":["RG-6-135-38"]}],"id":[{"id":"10.13039\/501100004054","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Neural Netw. Learning Syst."],"published-print":{"date-parts":[[2022,9]]},"DOI":"10.1109\/tnnls.2021.3055991","type":"journal-article","created":{"date-parts":[[2021,3,17]],"date-time":"2021-03-17T19:37:15Z","timestamp":1616009835000},"page":"4173-4183","source":"Crossref","is-referenced-by-count":70,"title":["Decision-Tree-Initialized Dendritic Neuron Model for Fast and Accurate Data Classification"],"prefix":"10.1109","volume":"33","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-3650-8450","authenticated-orcid":false,"given":"Xudong","family":"Luo","sequence":"first","affiliation":[{"name":"Teachers College for Vocational and Technical Education, Guangxi Normal University, Guilin, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4368-1443","authenticated-orcid":false,"given":"Xiaohao","family":"Wen","sequence":"additional","affiliation":[{"name":"Teachers College for Vocational and Technical Education, Guangxi Normal University, Guilin, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5408-8752","authenticated-orcid":false,"given":"MengChu","family":"Zhou","sequence":"additional","affiliation":[{"name":"Department of Electrical and Computer Engineering, New Jersey Institute of Technology, Newark, NJ, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8025-0453","authenticated-orcid":false,"given":"Abdullah","family":"Abusorrah","sequence":"additional","affiliation":[{"name":"Center of Research Excellence in Renewable Energy and Power Systems and the Department of Electrical and Computer Engineering, King Abdulaziz University, Jeddah, Saudi Arabia"}]},{"given":"Lukui","family":"Huang","sequence":"additional","affiliation":[{"name":"Guangxi University of Finance and Economics, Nanning, China"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1038\/nn.4301"},{"key":"ref2","article-title":"An entropy-based pruning method for CNN compression","volume-title":"arXiv:1706.05791","author":"Luo","year":"2017"},{"key":"ref3","first-page":"1379","article-title":"Dynamic network surgery for efficient DNNs","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Guo"},{"key":"ref4","first-page":"1135","article-title":"Learning both weights and connections for efficient neural network","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Han"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-01237-3_12"},{"key":"ref6","first-page":"2074","article-title":"Learning structured sparsity in deep neural networks","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Wen"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.155"},{"key":"ref8","article-title":"2PFPCE: Two-phase filter pruning based on conditional entropy","volume-title":"arXiv:1809.02220","author":"Min","year":"2018"},{"key":"ref9","first-page":"3","article-title":"ADAM-ADMM: A unified, systematic framework of structured weight pruning for DNNs","volume-title":"arXiv:1807.11091","volume":"2","author":"Zhang","year":"2018"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1561\/9781601984616"},{"key":"ref11","first-page":"392","article-title":"Dual averaging and proximal gradient descent for Online alternating direction multiplier method","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Suzuki"},{"key":"ref12","article-title":"Soft weight-sharing for neural network compression","volume-title":"arXiv:1702.04008","author":"Ullrich","year":"2017"},{"key":"ref13","article-title":"Learning sparse neural networks through L\u2080 regularization","volume-title":"arXiv:1712.01312","author":"Louizos","year":"2017"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/TNN.2004.836241"},{"key":"ref15","first-page":"164","article-title":"Second order derivatives for network pruning: Optimal brain surgeon","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","volume":"5","author":"Hassibi"},{"key":"ref16","first-page":"598","article-title":"Optimal brain damage","volume-title":"Proc. Int. Conf. Neural Inf. Process. Syst.","author":"Cun"},{"issue":"4","key":"ref17","first-page":"3","article-title":"Deep compression: Compressing deep neural networks with pruning, trained quantization and Huffman coding","volume":"56","author":"Han","year":"2016","journal-title":"Fiber"},{"key":"ref18","article-title":"Pruning convolutional neural networks for resource efficient inference","volume-title":"arXiv:1611.06440","author":"Molchanov","year":"2016"},{"issue":"3","key":"ref19","first-page":"625","article-title":"Why does unsupervised pre-training help deep learning?","volume":"11","author":"Bengio","year":"2010","journal-title":"J. Mach. Learn. Res."},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2009.191"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2019.2935384"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/TASE.2018.2865663"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1109\/TCSS.2020.3001517"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.21437\/Interspeech.2011-91"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-13972-2_8"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2014.2366792"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2016.2528162"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1109\/LGRS.2017.2771405"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.3389\/fnins.2018.00435"},{"issue":"2","key":"ref30","first-page":"15","article-title":"On suitability of online product sales prediction model based on convolutional neural networks","author":"Feiqiong","year":"2019","journal-title":"J. Northwest Minzu Univ., Philosophy Social Sci."},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1177\/2472555218818756"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2018.2869694"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.15388\/Informatica.2004.078"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1098\/rstb.1982.0084"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1002\/ecjc.1024"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2018.2846646"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2015.09.052"},{"key":"ref38","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1155\/2019\/7362931","article-title":"MrDNM: A novel mutual information-based dendritic neuron model","volume":"2019","author":"Qian","year":"2019","journal-title":"Comput. Intell. Neurosci."},{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2018.08.020"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1142\/S0129065719500126"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1587\/transinf.2014EDP7418"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1155\/2019\/8682124"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1155\/2018\/9390410"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2016.05.031"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.1109\/PIC.2016.7949463"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.1109\/UIC-ATC.2017.8397411"},{"key":"ref47","doi-asserted-by":"publisher","DOI":"10.1145\/3236009"},{"key":"ref48","doi-asserted-by":"publisher","DOI":"10.3321\/j.issn:0529-6579.2007.z1.029"},{"key":"ref49","article-title":"Towards better understanding of gradient-based attribution methods for deep neural networks","volume-title":"arXiv:1711.06104","author":"Ancona","year":"2017"},{"issue":"44","key":"ref50","first-page":"22071","article-title":"Interpretable machine learning: Definitions, methods, and applications","volume":"116","author":"Murdoch","year":"2019","journal-title":"Neurocomputing"},{"key":"ref51","article-title":"Regional tree regularization for interpretability in black box models","volume-title":"arXiv:1908.04494","author":"Wu","year":"2019"},{"key":"ref52","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2019.2944672"},{"key":"ref53","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2020.01.036"},{"key":"ref54","article-title":"Distilling a neural network into a soft decision tree","volume-title":"arXiv:1711.09784","author":"Frosst","year":"2017"},{"key":"ref55","article-title":"Adam: A method for stochastic optimization","volume-title":"arXiv:1412.6980","author":"Kingma","year":"2014"},{"key":"ref56","doi-asserted-by":"publisher","DOI":"10.1007\/BF00116251"},{"key":"ref57","doi-asserted-by":"publisher","DOI":"10.2307\/2530946"},{"key":"ref58","doi-asserted-by":"publisher","DOI":"10.1007\/s11222-009-9153-8"},{"key":"ref59","volume-title":"UCI Repository of Machine Learning Databases","author":"Merz","year":"1998"},{"key":"ref60","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-27733-7_299-3"},{"key":"ref61","doi-asserted-by":"publisher","DOI":"10.4249\/scholarpedia.1883"},{"key":"ref62","doi-asserted-by":"publisher","DOI":"10.1109\/IJCNN.1989.118638"},{"issue":"1","key":"ref63","first-page":"1","article-title":"Statistical comparisons of classifiers over multiple data sets","volume":"7","author":"Dem\u0161ar","year":"2006","journal-title":"J. Mach. Learn. Res."},{"key":"ref64","doi-asserted-by":"publisher","DOI":"10.1016\/j.csda.2009.04.009"},{"key":"ref65","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2009.187"},{"issue":"8","key":"ref66","first-page":"1","article-title":"ROC graphs: Notes and practical considerations for data mining researchers","volume":"31","author":"Fawcett","year":"2009","journal-title":"Mach. Learn."},{"key":"ref67","doi-asserted-by":"publisher","DOI":"10.1118\/1.1429239"},{"key":"ref68","doi-asserted-by":"publisher","DOI":"10.1007\/BF01062525"},{"key":"ref69","doi-asserted-by":"publisher","DOI":"10.1007\/s10732-008-9080-4"},{"key":"ref70","doi-asserted-by":"publisher","DOI":"10.1214\/aoms\/1177704575"},{"key":"ref71","doi-asserted-by":"publisher","DOI":"10.1198\/tech.2001.s629"},{"key":"ref72","doi-asserted-by":"publisher","DOI":"10.2991\/iccnce.2013.121"},{"key":"ref73","doi-asserted-by":"publisher","DOI":"10.1137\/140990309"},{"key":"ref74","doi-asserted-by":"publisher","DOI":"10.1109\/TCYB.2016.2606104"},{"key":"ref75","doi-asserted-by":"publisher","DOI":"10.1109\/JAS.2019.1911447"},{"key":"ref76","doi-asserted-by":"publisher","DOI":"10.1109\/JAS.2017.7510817"},{"key":"ref77","doi-asserted-by":"publisher","DOI":"10.1109\/JAS.2021.1003865"},{"key":"ref78","doi-asserted-by":"publisher","DOI":"10.1109\/TCSS.2019.2931186"},{"key":"ref79","doi-asserted-by":"publisher","DOI":"10.1109\/JAS.2020.1003465"},{"key":"ref80","doi-asserted-by":"publisher","DOI":"10.1109\/TITS.2019.2958741"}],"container-title":["IEEE Transactions on Neural Networks and Learning Systems"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/5962385\/9872163\/09380661.pdf?arnumber=9380661","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,1,9]],"date-time":"2024-01-09T23:12:40Z","timestamp":1704841960000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9380661\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,9]]},"references-count":80,"journal-issue":{"issue":"9"},"URL":"https:\/\/doi.org\/10.1109\/tnnls.2021.3055991","relation":{},"ISSN":["2162-237X","2162-2388"],"issn-type":[{"value":"2162-237X","type":"print"},{"value":"2162-2388","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,9]]}}}