{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,9,13]],"date-time":"2025-09-13T16:41:06Z","timestamp":1757781666773,"version":"3.28.0"},"reference-count":40,"publisher":"IEEE","license":[{"start":{"date-parts":[[2022,7,18]],"date-time":"2022-07-18T00:00:00Z","timestamp":1658102400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2022,7,18]],"date-time":"2022-07-18T00:00:00Z","timestamp":1658102400000},"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":[[2022,7,18]]},"DOI":"10.1109\/ijcnn55064.2022.9892671","type":"proceedings-article","created":{"date-parts":[[2022,9,30]],"date-time":"2022-09-30T19:56:04Z","timestamp":1664567764000},"page":"1-8","source":"Crossref","is-referenced-by-count":3,"title":["Accuracy Evaluation of Transposed Convolution-Based Quantized Neural Networks"],"prefix":"10.1109","author":[{"given":"Cristian","family":"Sestito","sequence":"first","affiliation":[{"name":"University of Calabria,Department of Informatics, Modeling, Electronics and System Engineering,Rende,Italy"}]},{"given":"Stefania","family":"Perri","sequence":"additional","affiliation":[{"name":"University of Calabria,Department of Mechanical, Energy and Management Engineering,Rende,Italy"}]},{"given":"Robert","family":"Stewart","sequence":"additional","affiliation":[{"name":"Heriot-Watt University,Department of Computer Science,Edinburgh,United Kingdom"}]}],"member":"263","reference":[{"journal-title":"Nips 2016 tutorial Generative adversarial networks","year":"2016","author":"goodfellow","key":"ref39"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1109\/5.726791"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2015.7298594"},{"key":"ref32","first-page":"6629","article-title":"GANs Trained by a Two Time-Scale Update Rule Converge to a Local Nash Equilibrium","author":"heusel","year":"2017","journal-title":"Proc Conf Neural Inf Process Syst (NIPS)"},{"key":"ref31","first-page":"2226","article-title":"Improved techniques for training GANs","author":"salimans","year":"2016","journal-title":"Proc Conf Neural Inf Process Syst (NIPS)"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.350"},{"key":"ref37","article-title":"Open Acccess dataset for the paper &#x201C;Accuracy Evalution of Transposed Convolution-Based Quantized Neural Networks","author":"sestito","year":"0","journal-title":"IEEE IJCNN"},{"journal-title":"NVIDIA&#x00AE; Tesla&#x00AE; K80","year":"0","key":"ref36"},{"journal-title":"NVIDIA&#x00AE; Tesla&#x00AE; T4","year":"0","key":"ref35"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2009.5206848"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1145\/3242897"},{"journal-title":"A note on the inception score","year":"2018","author":"barratt","key":"ref40"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-78890-6_3"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/FPL.2018.00024"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.3390\/electronics10040396"},{"key":"ref14","article-title":"Very deep convolutional networks for large-scale image recognition","author":"simonyan","year":"2015","journal-title":"Proc of the 3rd Int Conf on Learning Representations (ICLR 2015)"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.5201\/ipol.2011.g_lmii"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2015.178"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/FPL.2019.00037"},{"key":"ref18","first-page":"234","article-title":"U-Net: Convolutional Networks for Biomedical Image Segmentation","author":"ronneberger","year":"2015","journal-title":"Proc 18th Int Conf Medical Image Computing and Computer-Assisted Intervention (MICCAI 2015)"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.3390\/jimaging7100210"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2015.425"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/JIOT.2016.2579198"},{"journal-title":"Learning multiple layers of features from tiny images","year":"2009","author":"krizhevsky","key":"ref27"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/MCI.2018.2840738"},{"journal-title":"Intel&#x00AE; Movidius&#x2122; Vision Processing Units (VPUs)","year":"0","key":"ref6"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2012.6248092"},{"key":"ref5","first-page":"1","article-title":"Deep Neural Network Approximation for Custom Hardware: Where We've Been, Where We're Going","volume":"52","author":"wang","year":"2019","journal-title":"ACM Comput Sur"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/IISWC47752.2019.9042000"},{"journal-title":"Edge TPU Google's Purpose-Built ASIC Designed to Run Inference at the Edge","year":"0","key":"ref7"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1038\/s42256-020-0217-y"},{"key":"ref9","article-title":"Contrastive representation distillation","author":"tian","year":"2020","journal-title":"Proc 8th Int Conf on Learning Representations (ICLR 2020) Virtual"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2019.2956508"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2020.107338"},{"key":"ref22","article-title":"Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks","author":"radford","year":"2016","journal-title":"Proc 4th Int Conf on Learning Representations (ICLR 2016)"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/ICTC52510.2021.9620912"},{"key":"ref24","first-page":"6869","article-title":"Quantized Neural Networks: Training Neural Networks with Low Precision Weights and Activations","volume":"18","author":"hubara","year":"2017","journal-title":"The Journal of Machine Learning Research"},{"journal-title":"Xilinx\/brevitas","year":"0","author":"pappalardo","key":"ref23"},{"journal-title":"Fashion-mnist a novel image dataset for benchmarking machine learning algorithms","year":"2017","author":"xiao","key":"ref26"},{"journal-title":"The MNIST Database of Handwritten Digits","year":"0","author":"lecun","key":"ref25"}],"event":{"name":"2022 International Joint Conference on Neural Networks (IJCNN)","start":{"date-parts":[[2022,7,18]]},"location":"Padua, Italy","end":{"date-parts":[[2022,7,23]]}},"container-title":["2022 International Joint Conference on Neural Networks (IJCNN)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/9891857\/9889787\/09892671.pdf?arnumber=9892671","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,11,3]],"date-time":"2022-11-03T23:00:53Z","timestamp":1667516453000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9892671\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,7,18]]},"references-count":40,"URL":"https:\/\/doi.org\/10.1109\/ijcnn55064.2022.9892671","relation":{},"subject":[],"published":{"date-parts":[[2022,7,18]]}}}