{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,2,21]],"date-time":"2025-02-21T22:11:20Z","timestamp":1740175880892,"version":"3.37.3"},"reference-count":49,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"2","license":[{"start":{"date-parts":[[2024,4,1]],"date-time":"2024-04-01T00:00:00Z","timestamp":1711929600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2024,4,1]],"date-time":"2024-04-01T00:00:00Z","timestamp":1711929600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2024,4,1]],"date-time":"2024-04-01T00:00:00Z","timestamp":1711929600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"name":"National Key Research &#x0026; Development Program of China","award":["2018YFB1003900"],"award-info":[{"award-number":["2018YFB1003900"]}]},{"DOI":"10.13039\/501100004193","name":"Nanjing University of Aeronautics and Astronautics","doi-asserted-by":"publisher","award":["xcxjh20221613"],"award-info":[{"award-number":["xcxjh20221613"]}],"id":[{"id":"10.13039\/501100004193","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61602267","61402229"],"award-info":[{"award-number":["61602267","61402229"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Big Data"],"published-print":{"date-parts":[[2024,4]]},"DOI":"10.1109\/tbdata.2023.3334648","type":"journal-article","created":{"date-parts":[[2023,11,20]],"date-time":"2023-11-20T19:34:31Z","timestamp":1700508871000},"page":"132-145","source":"Crossref","is-referenced-by-count":0,"title":["FATS: Feature Distribution Analysis-Based Test Selection for Deep Learning Enhancement"],"prefix":"10.1109","volume":"10","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-1810-1216","authenticated-orcid":false,"given":"Li","family":"Li","sequence":"first","affiliation":[{"name":"College of Computer Science and Technology, Nanjing University of Aeronautics and Astronautics, Nanjing, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0698-7307","authenticated-orcid":false,"given":"Chuanqi","family":"Tao","sequence":"additional","affiliation":[{"name":"College of Computer Science and Technology, Nanjing University of Aeronautics and Astronautics, Nanjing, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5286-874X","authenticated-orcid":false,"given":"Hongjing","family":"Guo","sequence":"additional","affiliation":[{"name":"College of Computer Science and Technology, Nanjing University of Aeronautics and Astronautics, Nanjing, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8437-6640","authenticated-orcid":false,"given":"Jingxuan","family":"Zhang","sequence":"additional","affiliation":[{"name":"College of Computer Science and Technology, Nanjing University of Aeronautics and Astronautics, Nanjing, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5165-5080","authenticated-orcid":false,"given":"Xiaobing","family":"Sun","sequence":"additional","affiliation":[{"name":"School of Information Engineering, Yangzhou University, Jiangsu, China"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/TBDATA.2017.2680460"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.90"},{"article-title":"Achieving human parity in conversational speech recognition","year":"2016","author":"Wayne","key":"ref3"},{"article-title":"End to end learning for self-driving cars","year":"2016","author":"Bojarski","key":"ref4"},{"key":"ref5","first-page":"3104","article-title":"Sequence to sequence learning with neural networks","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Sutskever","year":"2014"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/TBDATA.2016.2576470"},{"issue":"3","key":"ref7","article-title":"Self-driving uber car kills pedestrian in Arizona, where robots roam","volume":"19","author":"Wakabayashi","year":"2018","journal-title":"New York Times"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1145\/3511598"},{"key":"ref9","first-page":"1041","article-title":"Cats are not fish: Deep learning testing calls for out-of-distribution awareness","volume-title":"Proc. IEEE\/ACM 35th Int. Conf. Automated Softw. Eng.","author":"Berend","year":"2020"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/ICSE43902.2021.00032"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1145\/3338906.3338930"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1145\/3510003.3510232"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1145\/3395363.3397357"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1145\/219587.219592"},{"key":"ref15","first-page":"410","article-title":"Multiple-boundary clustering and prioritization to promote neural network retraining","volume-title":"Proc. IEEE\/ACM 35th Int. Conf. Automated Softw. Eng.","author":"Shen","year":"2020"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/ICSE.2019.00108"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1561\/1500000016"},{"article-title":"The mnist database of handwritten digits","year":"1998","author":"LeCun","key":"ref18"},{"issue":"4","key":"ref19","article-title":"Learning multiple layers of features from tiny images","volume":"1","author":"Krizhevsky","year":"2009"},{"key":"ref20","article-title":"Reading digits in natural images with unsupervised feature learning","volume-title":"Proc. NIPS Workshop Deep Learn. Unsupervised Feature Learn.","author":"Yuval","year":"2011"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/5.726791"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2015.7298958"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2016.12.038"},{"key":"ref24","article-title":"Active learning for convolutional neural networks: A core-set approach","volume-title":"Proc. Int. Conf. Learn. Representations","author":"Sener","year":"2018"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00018"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1109\/ICSE48619.2023.00092"},{"key":"ref27","first-page":"7824","article-title":"Debugging and explaining metric learning approaches: An influence function based perspective","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","volume":"35","author":"Liu","year":"2022"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1145\/3417330"},{"issue":"3","key":"ref29","first-page":"237","article-title":"Active learning literature survey","volume":"10","author":"Settles","year":"1995","journal-title":"Science"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1145\/2911451.2914798"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1145\/3394112"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.1984.4767478"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.21105\/joss.00205"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1109\/TBDATA.2017.2742530"},{"key":"ref35","first-page":"2288","article-title":"Examples are not enough, learn to criticize! criticism for interpretability","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Kim","year":"2016"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1145\/3490489"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1145\/2939672.2939785"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1016\/j.eng.2019.12.012"},{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1145\/3180155.3180220"},{"article-title":"Explaining and harnessing adversarial examples","year":"2014","author":"Goodfellow","key":"ref40"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1201\/9781351251389-8"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1109\/EuroSP.2016.36"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1109\/SP.2017.49"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2015.291"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.1109\/SANER.2018.8330212"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.1007\/978-1-4612-4380-9_16"},{"key":"ref47","first-page":"1","article-title":"Exploring methods for evaluating group differences on the NSSE and other surveys: Are the t-test and cohen\u2019sd indices the most appropriate choices","volume-title":"Proc. Annu. Meeting Southern Assoc. Institutional Res.","author":"Romano","year":"2006"},{"key":"ref48","doi-asserted-by":"publisher","DOI":"10.1145\/1273496.1273513"},{"key":"ref49","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2018.05.083"}],"container-title":["IEEE Transactions on Big Data"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/6687317\/10472159\/10323141.pdf?arnumber=10323141","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,3,26]],"date-time":"2024-03-26T12:46:49Z","timestamp":1711457209000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10323141\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,4]]},"references-count":49,"journal-issue":{"issue":"2"},"URL":"https:\/\/doi.org\/10.1109\/tbdata.2023.3334648","relation":{},"ISSN":["2332-7790","2372-2096"],"issn-type":[{"type":"electronic","value":"2332-7790"},{"type":"electronic","value":"2372-2096"}],"subject":[],"published":{"date-parts":[[2024,4]]}}}