{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,2,21]],"date-time":"2025-02-21T01:43:07Z","timestamp":1740102187339,"version":"3.37.3"},"reference-count":29,"publisher":"IEEE","license":[{"start":{"date-parts":[[2023,6,19]],"date-time":"2023-06-19T00:00:00Z","timestamp":1687132800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2023,6,19]],"date-time":"2023-06-19T00:00:00Z","timestamp":1687132800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"DOI":"10.13039\/501100003725","name":"National Research Foundation of Korea","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100003725","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100010002","name":"Ministry of Education","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100010002","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2023,6,19]]},"DOI":"10.1109\/isie51358.2023.10228170","type":"proceedings-article","created":{"date-parts":[[2023,8,31]],"date-time":"2023-08-31T17:30:24Z","timestamp":1693503024000},"page":"1-6","source":"Crossref","is-referenced-by-count":1,"title":["DenseNetx: Efficient DenseNets for Remote Scene Classification without Pretraining"],"prefix":"10.1109","author":[{"given":"Russo Mohammad Ashraf","family":"Uddin","sequence":"first","affiliation":[{"name":"University of Ulsan,Department of Electrical, Electronic and Computer Engineering,Ulsan,Korea"}]},{"given":"Tien-Dat","family":"Tran","sequence":"additional","affiliation":[{"name":"University of Ulsan,Department of Electrical, Electronic and Computer Engineering,Ulsan,Korea"}]},{"given":"Ge","family":"Cao","sequence":"additional","affiliation":[{"name":"University of Ulsan,Department of Electrical, Electronic and Computer Engineering,Ulsan,Korea"}]},{"given":"Kang-Hyun","family":"Jo","sequence":"additional","affiliation":[{"name":"University of Ulsan,Department of Electrical, Electronic and Computer Engineering,Ulsan,Korea"}]}],"member":"263","reference":[{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1007\/s11119-022-09938-8"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1016\/j.rse.2019.111322"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2021.106921"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1145\/3388818.3389160"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1126\/science.1244693"},{"key":"ref10","article-title":"RTMDet: An Empirical Study of Designing Real-Time Object Detectors","author":"lyu","year":"2022","journal-title":"arXiv preprint arXiv 2212 07784"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1145\/1553374.1553453"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1016\/j.isprsjprs.2023.01.014"},{"key":"ref17","first-page":"1","article-title":"Parallel DenseNet: A Deep Convolutional Neural Network with Parallel Connections","author":"huang","year":"2018","journal-title":"Proceedings of the IEEE International Conference on Multimedia and Expo (ICME)"},{"key":"ref16","first-page":"540","article-title":"DenseNet-BCNN: DenseNet with Bottleneck Channels and Binary Connect Convolutional Layers","author":"ding","year":"2018","journal-title":"Proceedings of the 2nd International Conference on Image Vision and Computing (ICIVC)"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00326"},{"key":"ref18","first-page":"1577","article-title":"DenseNet-SI: DenseNet with Scale Invariant Convolutional Layers","author":"liu","year":"2021","journal-title":"Proceedings of the IEEE International Conference on Image Processing (ICIP)"},{"key":"ref24","first-page":"6105","article-title":"EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks","author":"tan","year":"2019","journal-title":"Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00716"},{"key":"ref26","article-title":"ProxylessNAS: Direct Neural Architecture Search on Target Task and Hardware","author":"cai","year":"2019","journal-title":"Proceedings of the International Conference on Learning Representations"},{"key":"ref25","article-title":"SqueezeNet: AlexNet-level accuracy with 50x fewer parameters and <0.5 MB model size","author":"iandola","year":"2016","journal-title":"arXiv preprint arXiv 1602 07360"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1109\/CVPRW.2019.00103"},{"key":"ref22","first-page":"1387","article-title":"MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications","author":"howard","year":"2017","journal-title":"Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.195"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.90"},{"key":"ref27","article-title":"On the Variance of the Adaptive Learning Rate and Beyond","author":"liu","year":"2020","journal-title":"International Conference on Learning Representations"},{"key":"ref29","article-title":"Multi-scale context aggregation by dilated convolutions","author":"fisher","year":"2015","journal-title":"arXiv preprint arXiv 1511 07122"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00502"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.143"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.243"},{"key":"ref4","article-title":"Very deep convolutional networks for large-scale image recognition","author":"simonyan","year":"2015","journal-title":"Proceedings of the International Conference on Learning Representations"},{"key":"ref3","first-page":"1097","article-title":"Imagenet classification with deep convolutional neural networks","author":"krizhevsky","year":"2012","journal-title":"Advances in Neural Information Processing Systems 25"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2015.7298965"},{"key":"ref5","first-page":"91","article-title":"Faster R-CNN: Towards RealTime Object Detection with Region Proposal Networks","author":"ren","year":"2015","journal-title":"Advances in Neural IInformation Processing Systems"}],"event":{"name":"2023 IEEE 32nd International Symposium on Industrial Electronics (ISIE)","start":{"date-parts":[[2023,6,19]]},"location":"Helsinki, Finland","end":{"date-parts":[[2023,6,21]]}},"container-title":["2023 IEEE 32nd International Symposium on Industrial Electronics (ISIE)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/10227852\/10227910\/10228170.pdf?arnumber=10228170","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,9,25]],"date-time":"2023-09-25T17:53:04Z","timestamp":1695664384000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10228170\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,6,19]]},"references-count":29,"URL":"https:\/\/doi.org\/10.1109\/isie51358.2023.10228170","relation":{},"subject":[],"published":{"date-parts":[[2023,6,19]]}}}