{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,25]],"date-time":"2026-10-25T08:34:40Z","timestamp":1792917280096,"version":"4.5.0"},"reference-count":29,"publisher":"IEEE","license":[{"start":{"date-parts":[[2020,10,1]],"date-time":"2020-10-01T00:00:00Z","timestamp":1601510400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2020,10,1]],"date-time":"2020-10-01T00:00:00Z","timestamp":1601510400000},"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":[[2020,10]]},"DOI":"10.1109\/iscas45731.2020.9180844","type":"proceedings-article","created":{"date-parts":[[2020,9,29]],"date-time":"2020-09-29T09:22:27Z","timestamp":1601371347000},"page":"1-5","source":"Crossref","is-referenced-by-count":16,"title":["A Convolutional Neural Network Accelerator Architecture with Fine-Granular Mixed Precision Configurability"],"prefix":"10.1109","author":[{"given":"Xian","family":"Zhou","sequence":"first","affiliation":[{"name":"College of Information Science and Electronic Engineering, Zhejiang University, Hangzhou, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Li","family":"Zhang","sequence":"additional","affiliation":[{"name":"College of Information Science and Electronic Engineering, Zhejiang University, Hangzhou, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Chuliang","family":"Guo","sequence":"additional","affiliation":[{"name":"College of Information Science and Electronic Engineering, Zhejiang University, Hangzhou, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xunzhao","family":"Yin","sequence":"additional","affiliation":[{"name":"College of Information Science and Electronic Engineering, Zhejiang University, Hangzhou, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Cheng","family":"Zhuo","sequence":"additional","affiliation":[{"name":"College of Information Science and Electronic Engineering, Zhejiang University, Hangzhou, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"263","reference":[{"key":"ref1","article-title":"Very deep convolutional networks for large-scale image recognition","volume-title":"Proc. CVPR","author":"Simonyan"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.90"},{"key":"ref3","article-title":"End to end learning for self-driving cars","volume-title":"Proc. CVPR","author":"Bojarski"},{"key":"ref4","article-title":"MobiRNN: Efficient recurrent neural network execution on mobile GPU","volume-title":"Proc. ACM","author":"Qingqing"},{"key":"ref5","article-title":"FBNA: A Fully Binarized Neural Network Accelerator","volume-title":"Proc. FPL","author":"Peng"},{"key":"ref6","article-title":"High performance binary neural networks on the xeon+FPGATM platform","volume-title":"Proc. FPL","author":"Moss"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1145\/3296957.3173212"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1145\/3240765.3240775"},{"key":"ref9","article-title":"Cloud-DNN: An Open Framework for Mapping DNN Models to Cloud FPGAs","volume-title":"Proc. ACM","author":"Yao"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/JSSC.2016.2616357"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/VLSIC.2018.8502388"},{"key":"ref12","article-title":"Envision: A 0.26-to-10 TOPS\/W subword-parallel dynamic-voltage-accuracy-frequency-scalable convolutional neural network processor 28 nm FDSOI","volume-title":"Proc. ISSCC","author":"Moons"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/ISSCC.2017.7870350"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/JSSC.2018.2865489"},{"key":"ref15","article-title":"Mobilenets: Efficient convolutional neural networks for mobile vision applications","volume-title":"Proc. CVPR","author":"Howard"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-46493-0_32"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.48550\/ARXIV.1602.07360"},{"key":"ref18","article-title":"Effective quantization methods for recurrent neural networks","volume-title":"Proc. CVPR","author":"He"},{"key":"ref19","article-title":"Trained ternary quantization","volume-title":"Proc. ICLR","author":"Zhu"},{"key":"ref20","article-title":"Deep convolutional neural network inference with floating-point weights and fixed-point activations","volume-title":"Proc. CVPR","author":"Lai"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.23919\/DATE.2017.7927224"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.23919\/DATE.2017.7926982"},{"key":"ref23","article-title":"Efficient Hybrid Network Architectures for Extremely Quantized Neural Networks Enabling Intelligence at the Edge","volume-title":"Proc. ACM","author":"Chakraborty"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1145\/3240765.3240801"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1109\/tnnls.2018.2852335"},{"key":"ref26","article-title":"A scalable multi-TeraOPS deep learning processor core for AI training and inference","volume-title":"Proc. VLSI","author":"Fleischer"},{"key":"ref27","article-title":"A 1.06 to 5.09 TOPS\/W reconfigurable hybrid neural network processor","volume-title":"Proc. VLSI","author":"Yin"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1145\/1816038.1815968"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1109\/ISSCC.2014.6757323"}],"event":{"name":"2020 IEEE International Symposium on Circuits and Systems (ISCAS)","location":"Seville, Spain","start":{"date-parts":[[2020,10,12]]},"end":{"date-parts":[[2020,10,14]]}},"container-title":["2020 IEEE International Symposium on Circuits and Systems (ISCAS)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/9179985\/9180369\/09180844.pdf?arnumber=9180844","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,10,25]],"date-time":"2026-10-25T07:35:55Z","timestamp":1792913755000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9180844\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,10]]},"references-count":29,"URL":"https:\/\/doi.org\/10.1109\/iscas45731.2020.9180844","relation":{},"subject":[],"published":{"date-parts":[[2020,10]]}}}