{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,26]],"date-time":"2026-02-26T16:09:13Z","timestamp":1772122153427,"version":"3.50.1"},"reference-count":43,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","license":[{"start":{"date-parts":[[2021,1,1]],"date-time":"2021-01-01T00:00:00Z","timestamp":1609459200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/legalcode"}],"funder":[{"DOI":"10.13039\/100006754","name":"U.S. Army Research Laboratory through Cooperative Agreement","doi-asserted-by":"publisher","award":["W911NF-10-2-0022"],"award-info":[{"award-number":["W911NF-10-2-0022"]}],"id":[{"id":"10.13039\/100006754","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Open J. Circuits Syst."],"published-print":{"date-parts":[[2021]]},"DOI":"10.1109\/ojcas.2020.3043737","type":"journal-article","created":{"date-parts":[[2021,1,25]],"date-time":"2021-01-25T22:19:15Z","timestamp":1611613155000},"page":"182-195","source":"Crossref","is-referenced-by-count":12,"title":["An Energy Efficient EdgeAI Autoencoder Accelerator for Reinforcement Learning"],"prefix":"10.1109","volume":"2","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-5551-2124","authenticated-orcid":false,"given":"Nitheesh Kumar","family":"Manjunath","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5402-0988","authenticated-orcid":false,"given":"Aidin","family":"Shiri","sequence":"additional","affiliation":[]},{"given":"Morteza","family":"Hosseini","sequence":"additional","affiliation":[]},{"given":"Bharat","family":"Prakash","sequence":"additional","affiliation":[]},{"given":"Nicholas R.","family":"Waytowich","sequence":"additional","affiliation":[]},{"given":"Tinoosh","family":"Mohsenin","sequence":"additional","affiliation":[]}],"member":"263","reference":[{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.3390\/app8040504"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.23919\/FPL.2017.8056850"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1109\/ISQED.2019.8697574"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1088\/2632-2153\/aba042"},{"key":"ref31","author":"chevalier-boisvert","year":"2018","journal-title":"Gym-Miniworld Environment for Openai Gym"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.90"},{"key":"ref37","first-page":"37","article-title":"14nm educational design kit: Capabilities deployment and future","author":"melikyan","year":"2018","journal-title":"Proc Small Syst Simul Symp"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1109\/CENIM.2018.8710854"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1145\/2684746.2689060"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1145\/3005448"},{"key":"ref10","first-page":"262","article-title":"Sim-to-real robot learning from pixels with progressive nets","author":"rusu","year":"2017","journal-title":"Proc Conf Robot Learn"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1109\/MSP.2017.2743240"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-43089-4_44"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/ICRA.2019.8793742"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1145\/3361682"},{"key":"ref14","article-title":"A low complexity automated multi-channel EEG artifact detection using EEGNet","author":"khatwani","year":"2019","journal-title":"Proc IEEE EMBS Conf Neural Eng"},{"key":"ref15","first-page":"105","article-title":"A low-power LSTM processor for multi-channel brain EEG artifact detection","author":"rashid","year":"2020","journal-title":"Proc Int Symp Quality Electronic Design (ISQED)"},{"key":"ref16","first-page":"1","article-title":"Neural networks for pulmonary disease diagnosis using auditory and demographic information","author":"hosseini","year":"2020","journal-title":"Proc 3rd ACM SIGKDD Int Workshop Epidemiol Meets Data Min Knowl Disc"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/FCCM.2015.50"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1145\/3386263.3407652"},{"key":"ref19","first-page":"153","article-title":"Guiding safe reinforcement learning policies using structured language constraints","author":"prakash","year":"2020","journal-title":"Proc SafeAI Workshop 34th AAAI Conf Artif Intell"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1109\/IJCNN.2017.7966166"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1145\/3299874.3319493"},{"key":"ref27","author":"zhu","year":"2016","journal-title":"Trained ternary quantization"},{"key":"ref3","author":"theis","year":"2017","journal-title":"Lossy image compression with compressive autoencoders"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1007\/11552246_35"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1016\/j.neunet.2018.01.010"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/ROBOT.2004.1307456"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1038\/nature24270"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1613\/jair.859"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/ICDMW.2016.0041"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1038\/nature14236"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/ICRA.2017.7989381"},{"key":"ref20","year":"2020","journal-title":"NVIDIA Jetson TX2"},{"key":"ref22","author":"raffin","year":"2019","journal-title":"Learning to Drive Smoothly in Minutes"},{"key":"ref21","author":"sutton","year":"2018","journal-title":"Reinforcement Learning An Introduction"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1145\/3323055"},{"key":"ref24","article-title":"Binary precision neural network manycore accelerator","author":"hosseini","year":"2020","journal-title":"ACM J Emerg Technol Comput Syst"},{"key":"ref41","author":"wang","year":"2018","journal-title":"A Survey of FPGA Based Deep Learning Accelerators Challenges and Opportunities"},{"key":"ref23","first-page":"4107","article-title":"Binarized neural networks","author":"hubara","year":"2016","journal-title":"Proc Adv Neural Inf Process Syst"},{"key":"ref26","author":"li","year":"2016","journal-title":"Ternary Weight Networks"},{"key":"ref43","first-page":"224","article-title":"Reinforcement learning based self-adaptive voltage-swing adjustment of 2.5 DI\/Os for many-core microprocessor and memory communication","author":"hantao","year":"2014","journal-title":"Proc IEEE\/ACM Int Conf Comput Aided Design (ICCAD)"},{"key":"ref25","first-page":"3123","article-title":"BinaryConnect: Training deep neural networks with binary weights during propagations","author":"courbariaux","year":"2015","journal-title":"Proc Adv Neural Inf Process Syst"}],"container-title":["IEEE Open Journal of Circuits and Systems"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/8784029\/9314963\/09335309.pdf?arnumber=9335309","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2021,12,17]],"date-time":"2021-12-17T19:59:07Z","timestamp":1639771147000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9335309\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021]]},"references-count":43,"URL":"https:\/\/doi.org\/10.1109\/ojcas.2020.3043737","relation":{},"ISSN":["2644-1225"],"issn-type":[{"value":"2644-1225","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021]]}}}