{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,10,30]],"date-time":"2024-10-30T15:50:14Z","timestamp":1730303414016,"version":"3.28.0"},"reference-count":37,"publisher":"IEEE","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2018,4]]},"DOI":"10.1109\/vlsi-dat.2018.8373246","type":"proceedings-article","created":{"date-parts":[[2018,6,7]],"date-time":"2018-06-07T23:36:08Z","timestamp":1528414568000},"page":"1-3","source":"Crossref","is-referenced-by-count":5,"title":["Acceleration of neural network model execution on embedded systems"],"prefix":"10.1109","author":[{"given":"Chang-Jiun","family":"Chen","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Kai-Chun","family":"Chen","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"May-chen","family":"Martin-Kuo","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2015.7298594"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2016.2537340"},{"article-title":"Outrageously large neural networks: The sparselygated mixture-of-experts layer","year":"2017","author":"shazeer","key":"ref31"},{"key":"ref30","article-title":"How transferable are features in deep neural networks?","author":"yosinski","year":"2014","journal-title":"Advances in Neural Information Processing Systems 27 (NIPS&#x2019; 14) NIPS Foundation"},{"journal-title":"Fast training of convolutional networks through ffts","year":"2014","author":"mathieu","key":"ref37"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.435"},{"key":"ref35","article-title":"Deep pyramidal residual networks with separated stochastic depth","volume":"abs 1612 1230","author":"yamada","year":"2016","journal-title":"CoRR"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-46493-0_39"},{"key":"ref10","article-title":"Deep compression: Compressing deep neural networks with pruning, trained quantization and huffman coding","author":"han","year":"2016","journal-title":"International Conference on Learning Representations (ICLR)"},{"key":"ref11","article-title":"Towards the limit of network auantization","volume":"abs 1612 1543","author":"choi","year":"2016","journal-title":"CoRR"},{"key":"ref12","first-page":"3123","article-title":"Binaryconnect: Training deep neural networks with binary weights during propagations","author":"courbariaux","year":"2015","journal-title":"Advances in Neural Information Processing Systems 28 Annual Conference on Neural Information Processing Systems 2015"},{"key":"ref13","article-title":"Binarynet: Training deep neural networks with weights and activations constrained to +1 or - 1","volume":"abs 1602 2830","author":"courbariaux","year":"2016","journal-title":"CoRR"},{"key":"ref14","article-title":"Xnor-net: Imagenet classification using binary convolutional neural networks","author":"rastegari","year":"2016","journal-title":"ECCV"},{"key":"ref15","article-title":"Deep neural networks are robust to weight binarization and other nonlinear distortions","volume":"abs 1606 1981","author":"merolla","year":"2016","journal-title":"CoRR"},{"key":"ref16","article-title":"Loss-aware binarization of deep networks","volume":"abs 1611 1600","author":"hou","year":"2016","journal-title":"CoRR"},{"key":"ref17","article-title":"Soft weight-sharing for neural network compression","volume":"abs 1702 4008","author":"ullrich","year":"2017","journal-title":"CoRR"},{"key":"ref18","first-page":"1269","article-title":"Exploiting linear structure within convolutional networks for efficient evaluation","author":"denton","year":"2014","journal-title":"Advances in Neural Information Processing Systems 27"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.5244\/C.28.88"},{"key":"ref28","article-title":"Paying more attention to attention: Improving the performance of convolutional neural networks via attention transfer","volume":"abs 1612 3928","author":"zagoruyko","year":"2016","journal-title":"CoRR"},{"key":"ref4","article-title":"Fullyadaptive feature sharing in multi-task networks with applications in person attribute classification","volume":"abs 1611 5377","author":"lu","year":"2016","journal-title":"CoRR"},{"key":"ref27","article-title":"Net2net: Accelerating learning via knowledge transfer","volume":"abs 1511 5641","author":"chen","year":"2015","journal-title":"CoRR"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2014.220"},{"key":"ref6","article-title":"Compressing deep convolutional networks using vector quantization","volume":"abs 1412 6115","author":"gong","year":"2014","journal-title":"CoRR"},{"key":"ref29","first-page":"2549","article-title":"Dynamic capacity networks","author":"almahairi","year":"2016","journal-title":"Proceedings of the 33nd International Conference on Machine Learning ICML 2016"},{"key":"ref5","article-title":"Large scale distributed deen networks","author":"dean","year":"2012","journal-title":"NIPS"},{"key":"ref8","article-title":"Improving the speed of neural networks on cpus","author":"vanhoucke","year":"2011","journal-title":"Proc NIPS Workshop on Deep Learning and Unsupervised Feature Learning"},{"key":"ref7","article-title":"Quantized convolutional neural networks for mobile devices","author":"jiaxiang","year":"2016","journal-title":"IEEE Conference on Computer Vision and Pattern Recognition (CVPR)"},{"key":"ref2","article-title":"Very deep convolutional networks for large-scale image recognition","volume":"abs 1409 1556","author":"simonyan","year":"2014","journal-title":"CoRR"},{"key":"ref9","first-page":"1737","article-title":"Deep learning with limited numerical precision","volume":"37","author":"gupta","year":"2015","journal-title":"Proceedings of the 32Nd International Conference on International Conference on Machine Learning"},{"key":"ref1","article-title":"Imagenet classification with deep convolutional neural networks","author":"krizhevsky","year":"2012","journal-title":"NIPS"},{"key":"ref20","article-title":"Speeding-up convolutional neural networks using fine-tuned cpdecomnosition","volume":"abs 1412 6553","author":"lebedev","year":"2014","journal-title":"CoRR"},{"key":"ref22","first-page":"2654","article-title":"Do deep nets really need to be deep?","author":"ba","year":"2014","journal-title":"Advances in Neural Information Processing Systems 27 Annual Conference on Neural Information Processing Systems 2014"},{"key":"ref21","volume":"abs 1511 6067","author":"tai","year":"2015","journal-title":"Convolutional neural networks with low-rank regularization"},{"key":"ref24","article-title":"Fitnets: Hints for thin deep nets","volume":"abs 1412 6550","author":"romero","year":"2014","journal-title":"CoRR"},{"key":"ref23","article-title":"Distilling the knowledge in a neural network","volume":"abs 1503 2531","author":"hinton","year":"2015","journal-title":"CoRR"},{"key":"ref26","first-page":"3560","article-title":"Face model compression by distilling knowledge from neurons","author":"luo","year":"2016","journal-title":"Proc of the Thirtieth AAAI Conference on Artificial Intelligence"},{"key":"ref25","first-page":"3420","article-title":"Bayesian dark knowledge","author":"korattikara balan","year":"2015","journal-title":"Advances in Neural IInformation Processing Systems"}],"event":{"name":"2018 International Symposium on VLSI Design, Automation and Test (VLSI-DAT)","start":{"date-parts":[[2018,4,16]]},"location":"Hsinchu","end":{"date-parts":[[2018,4,19]]}},"container-title":["2018 International Symposium on VLSI Design, Automation and Test (VLSI-DAT)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/8370612\/8373223\/08373246.pdf?arnumber=8373246","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2018,6,26]],"date-time":"2018-06-26T00:17:41Z","timestamp":1529972261000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/8373246\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018,4]]},"references-count":37,"URL":"https:\/\/doi.org\/10.1109\/vlsi-dat.2018.8373246","relation":{},"subject":[],"published":{"date-parts":[[2018,4]]}}}