R. Manjunath, B.N Chandrashekar, B. Vinutha, Rahul Arya, Arindam Chatterjee
{"title":"统一的可解释AI框架,提高分类器性能","authors":"R. Manjunath, B.N Chandrashekar, B. Vinutha, Rahul Arya, Arindam Chatterjee","doi":"10.1109/GHCI47972.2019.9071811","DOIUrl":null,"url":null,"abstract":"Deep learning image classifiers are extensively used in document processing, activity monitoring, object recognition and separations etc. However, even the best classifiers are not free from errors. It would be very helpful if the errors that are pumped in to the system due to the classifier decisions are reduced. The framework comprises of heat map generation, attribute generation, text explanation generation and activation.","PeriodicalId":153240,"journal":{"name":"2019 Grace Hopper Celebration India (GHCI)","volume":"48 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Unified framework of Explainable AI to enhance classifier performance\",\"authors\":\"R. Manjunath, B.N Chandrashekar, B. Vinutha, Rahul Arya, Arindam Chatterjee\",\"doi\":\"10.1109/GHCI47972.2019.9071811\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Deep learning image classifiers are extensively used in document processing, activity monitoring, object recognition and separations etc. However, even the best classifiers are not free from errors. It would be very helpful if the errors that are pumped in to the system due to the classifier decisions are reduced. The framework comprises of heat map generation, attribute generation, text explanation generation and activation.\",\"PeriodicalId\":153240,\"journal\":{\"name\":\"2019 Grace Hopper Celebration India (GHCI)\",\"volume\":\"48 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2019 Grace Hopper Celebration India (GHCI)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/GHCI47972.2019.9071811\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 Grace Hopper Celebration India (GHCI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/GHCI47972.2019.9071811","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Unified framework of Explainable AI to enhance classifier performance
Deep learning image classifiers are extensively used in document processing, activity monitoring, object recognition and separations etc. However, even the best classifiers are not free from errors. It would be very helpful if the errors that are pumped in to the system due to the classifier decisions are reduced. The framework comprises of heat map generation, attribute generation, text explanation generation and activation.