{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,16]],"date-time":"2026-06-16T21:23:50Z","timestamp":1781645030973,"version":"3.54.5"},"reference-count":17,"publisher":"IEEE","license":[{"start":{"date-parts":[[2022,7,17]],"date-time":"2022-07-17T00:00:00Z","timestamp":1658016000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2022,7,17]],"date-time":"2022-07-17T00:00:00Z","timestamp":1658016000000},"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":[[2022,7,17]]},"DOI":"10.1109\/igarss46834.2022.9883815","type":"proceedings-article","created":{"date-parts":[[2022,9,28]],"date-time":"2022-09-28T16:12:24Z","timestamp":1664381544000},"page":"2570-2573","source":"Crossref","is-referenced-by-count":18,"title":["Explainable Analysis of Deep Learning Methods for Sar Image Classification"],"prefix":"10.1109","author":[{"given":"Shenghan","family":"Su","sequence":"first","affiliation":[{"name":"Shanghai Jiao Tong University,Shanghai Key Laboratory of Intelligent Sensing and Recognition,Shanghai,China,200240"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ziteng","family":"Cui","sequence":"additional","affiliation":[{"name":"Shanghai Jiao Tong University,Shanghai Key Laboratory of Intelligent Sensing and Recognition,Shanghai,China,200240"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Weiwei","family":"Guo","sequence":"additional","affiliation":[{"name":"Tongji University,Center of Digital Innovation,Shanghai,China,200092"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zenghui","family":"Zhang","sequence":"additional","affiliation":[{"name":"Shanghai Jiao Tong University,Shanghai Key Laboratory of Intelligent Sensing and Recognition,Shanghai,China,200240"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Wenxian","family":"Yu","sequence":"additional","affiliation":[{"name":"Shanghai Jiao Tong University,Shanghai Key Laboratory of Intelligent Sensing and Recognition,Shanghai,China,200240"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"263","reference":[{"key":"ref10","first-page":"3319","article-title":"Axiomatic attri-bution for deep networks","author":"sundararajan","year":"2017","journal-title":"Proceedings of the 34th In-ternational Conference on Machine Learning - Volume 70 ser ICML&#x2019; 17 JMLR org"},{"key":"ref11","author":"springenberg","year":"2014","journal-title":"Striving for simplicity The all convolutional net"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.74"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-46466-4_8"},{"key":"ref14","article-title":"On the (in)fidelity and sensitivity of ex-planations","author":"yeh","year":"2019","journal-title":"NeurIPS"},{"key":"ref15","author":"samek","year":"2020","journal-title":"Toward Interpretable Machine Learning Transparent Deep Neural Networks and Beyond"},{"key":"ref16","author":"paszke","year":"2019","journal-title":"Pytorch An imperative style high-performance deep learning library"},{"key":"ref17","author":"kokhlikyan","year":"2020","journal-title":"Captum A unified and generic model interpretability library for pytorch"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1038\/s41467-019-08987-4"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-70665-4_54"},{"key":"ref6","article-title":"Deep resid-ual learning for image recognition","author":"he","year":"2016","journal-title":"Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1016\/j.jag.2021.102520"},{"key":"ref8","article-title":"Deep in-side convolutional networks: Visualising image classi-fication models and saliency maps","author":"simonyan","year":"2014","journal-title":"In International Conference on Learning Representations Workshop"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/JSTARS.2019.2954850"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/LGRS.2016.2618840"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1561\/2000000039"},{"key":"ref9","first-page":"3145","article-title":"Learning important features through propagating activation differ-ences","author":"shrikumar","year":"2017","journal-title":"Proceedings of the 34th International Confer-ence on Machine Learning - Volume 70 ser ICML'17 JMLR org"}],"event":{"name":"IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium","location":"Kuala Lumpur, Malaysia","start":{"date-parts":[[2022,7,17]]},"end":{"date-parts":[[2022,7,22]]}},"container-title":["IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/9883023\/9883024\/09883815.pdf?arnumber=9883815","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,6,2]],"date-time":"2026-06-02T20:04:38Z","timestamp":1780430678000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9883815\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,7,17]]},"references-count":17,"URL":"https:\/\/doi.org\/10.1109\/igarss46834.2022.9883815","relation":{},"subject":[],"published":{"date-parts":[[2022,7,17]]}}}