{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,30]],"date-time":"2025-12-30T08:55:47Z","timestamp":1767084947609,"version":"3.41.0"},"publisher-location":"New York, NY, USA","reference-count":18,"publisher":"ACM","license":[{"start":{"date-parts":[[2021,6,22]],"date-time":"2021-06-22T00:00:00Z","timestamp":1624320000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"funder":[{"name":"Xilinx University Program (XUP)"}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2021,6,22]]},"DOI":"10.1145\/3453688.3461485","type":"proceedings-article","created":{"date-parts":[[2021,6,18]],"date-time":"2021-06-18T23:13:45Z","timestamp":1624058025000},"page":"247-252","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":10,"title":["DeepDive"],"prefix":"10.1145","author":[{"given":"Mohammadreza","family":"Baharani","sequence":"first","affiliation":[{"name":"University of North Carolina, Charlotte, Charlotte, NC, USA"}]},{"given":"Ushma","family":"Sunil","sequence":"additional","affiliation":[{"name":"University of North Carolina, Charlotte, Charlotte, NC, USA"}]},{"given":"Kaustubh","family":"Manohar","sequence":"additional","affiliation":[{"name":"University of North Carolina, Charlotte, Charlotte, NC, USA"}]},{"given":"Steven","family":"Furgurson","sequence":"additional","affiliation":[{"name":"University of North Carolina, Charlotte, Charlotte, NC, USA"}]},{"given":"Hamed","family":"Tabkhi","sequence":"additional","affiliation":[{"name":"University of North Carolina, Charlotte, Charlotte, NC, USA"}]}],"member":"320","published-online":{"date-parts":[[2021,6,22]]},"reference":[{"key":"e_1_3_2_3_1_1","unstructured":"[n.d.]. Xilinx AI Model Zoo. https:\/\/github.com\/Xilinx\/AI-Model-Zoo"},{"key":"e_1_3_2_3_2_1","doi-asserted-by":"publisher","DOI":"10.1145\/3242897"},{"key":"e_1_3_2_3_3_1","doi-asserted-by":"publisher","DOI":"10.1145\/2882903.2903741"},{"key":"e_1_3_2_3_4_1","doi-asserted-by":"publisher","DOI":"10.1109\/TCAD.2017.2705069"},{"key":"e_1_3_2_3_5_1","volume-title":"MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications. CoRR","author":"Howard Andrew G.","year":"2017","unstructured":"Andrew G. Howard, Menglong Zhu, Bo Chen, Dmitry Kalenichenko, Weijun Wang, Tobias Weyand, Marco Andreetto, and Hartwig Adam. 2017. MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications. CoRR, Vol. abs\/1704.04861 (2017). arxiv: 1704.04861"},{"key":"e_1_3_2_3_6_1","volume-title":"Quantization and Training of Neural Networks for Efficient Integer-Arithmetic-Only Inference. In 2018 IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2018","author":"Jacob Benoit","year":"2018","unstructured":"Benoit Jacob, Skirmantas Kligys, Bo Chen, Menglong Zhu, Matthew Tang, Andrew G. Howard, Hartwig Adam, and Dmitry Kalenichenko. 2018. Quantization and Training of Neural Networks for Efficient Integer-Arithmetic-Only Inference. In 2018 IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2018, Salt Lake City, UT, USA, June 18--22, 2018. 2704--2713."},{"key":"e_1_3_2_3_7_1","volume-title":"Electronic and Automation Control Conference (IAEAC)","volume":"1","author":"Liao J.","unstructured":"J. Liao, L. Cai, Y. Xu, and M. He. 2019. Design of Accelerator for MobileNet Convolutional Neural Network Based on FPGA. In 2019 IEEE 4th Advanced Information Technology, Electronic and Automation Control Conference (IAEAC), Vol. 1. 1392--1396."},{"key":"e_1_3_2_3_8_1","doi-asserted-by":"publisher","DOI":"10.1109\/MM.2019.2928962"},{"key":"e_1_3_2_3_9_1","doi-asserted-by":"publisher","DOI":"10.5555\/3195638.3195659"},{"key":"e_1_3_2_3_10_1","volume-title":"Proceedings of the 36th International Conference on Machine Learning, ICML 2019","author":"Tan Mingxing","year":"2019","unstructured":"Mingxing Tan and Quoc V. Le. 2019. EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks. In Proceedings of the 36th International Conference on Machine Learning, ICML 2019, 9-15 June 2019, Long Beach, California, USA. 6105--6114."},{"key":"e_1_3_2_3_11_1","doi-asserted-by":"publisher","DOI":"10.1145\/3020078.3021744"},{"key":"e_1_3_2_3_12_1","doi-asserted-by":"publisher","DOI":"10.1145\/3020078.3021791"},{"key":"e_1_3_2_3_13_1","doi-asserted-by":"publisher","DOI":"10.1145\/2897937.2898003"},{"key":"e_1_3_2_3_14_1","doi-asserted-by":"publisher","DOI":"10.1145\/3061639.3062207"},{"key":"e_1_3_2_3_15_1","doi-asserted-by":"publisher","unstructured":"Di Wu Yu Zhang Xijie Jia Lu Tian Tianping Li Lingzhi Sui Dongliang Xie and Yi Shan. 2019. A High-Performance CNN Processor Based on FPGA for MobileNets. 136--143. https:\/\/doi.org\/10.1109\/FPL.2019.00030","DOI":"10.1109\/FPL.2019.00030"},{"key":"e_1_3_2_3_16_1","doi-asserted-by":"publisher","DOI":"10.1145\/2966986.2967011"},{"key":"e_1_3_2_3_17_1","doi-asserted-by":"publisher","DOI":"10.1145\/3240765.3240801"},{"key":"e_1_3_2_3_18_1","doi-asserted-by":"publisher","unstructured":"Ruizhe Zhao Ho-Cheung Ng Wayne Luk and Xinyu Niu. 2018. Towards Efficient Convolutional Neural Network for Domain-Specific Applications on FPGA. 147--1477. https:\/\/doi.org\/10.1109\/FPL.2018.00033","DOI":"10.1109\/FPL.2018.00033"}],"event":{"name":"GLSVLSI '21: Great Lakes Symposium on VLSI 2021","sponsor":["SIGDA ACM Special Interest Group on Design Automation"],"location":"Virtual Event USA","acronym":"GLSVLSI '21"},"container-title":["Proceedings of the 2021 Great Lakes Symposium on VLSI"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3453688.3461485","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3453688.3461485","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T20:47:49Z","timestamp":1750193269000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3453688.3461485"}},"subtitle":["An Integrative Algorithm\/Architecture Co-Design for Deep Separable Convolutional Neural Networks"],"short-title":[],"issued":{"date-parts":[[2021,6,22]]},"references-count":18,"alternative-id":["10.1145\/3453688.3461485","10.1145\/3453688"],"URL":"https:\/\/doi.org\/10.1145\/3453688.3461485","relation":{},"subject":[],"published":{"date-parts":[[2021,6,22]]},"assertion":[{"value":"2021-06-22","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}