{"title":"基于网络压缩的猫狗图像快速识别","authors":"Peng Wang, Mengya Chen","doi":"10.1117/12.2654130","DOIUrl":null,"url":null,"abstract":"Cat and dog recognition is a classic problem in the field of image recognition. This paper proposes a fast detection algorithm FAST-CD-Classification-Net for this problem. The algorithm improves F1 from 0.7299 to 0.9875 with the help of residual structure; The product acceleration network reduces the running time from 0.025s to 0.008s without significantly reducing the accuracy. Experiments on the data set CD-KAGGLE show that the accuracy and robustness of the recognition algorithm designed in this paper are better than other algorithms.","PeriodicalId":32903,"journal":{"name":"JITeCS Journal of Information Technology and Computer Science","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2022-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Fast recognition of cat and dog images based on network compression\",\"authors\":\"Peng Wang, Mengya Chen\",\"doi\":\"10.1117/12.2654130\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Cat and dog recognition is a classic problem in the field of image recognition. This paper proposes a fast detection algorithm FAST-CD-Classification-Net for this problem. The algorithm improves F1 from 0.7299 to 0.9875 with the help of residual structure; The product acceleration network reduces the running time from 0.025s to 0.008s without significantly reducing the accuracy. Experiments on the data set CD-KAGGLE show that the accuracy and robustness of the recognition algorithm designed in this paper are better than other algorithms.\",\"PeriodicalId\":32903,\"journal\":{\"name\":\"JITeCS Journal of Information Technology and Computer Science\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-12-08\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"JITeCS Journal of Information Technology and Computer Science\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1117/12.2654130\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"JITeCS Journal of Information Technology and Computer Science","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1117/12.2654130","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
摘要
猫狗识别是图像识别领域的一个经典问题。针对这一问题，本文提出了一种快速检测算法fast - cd - classification - net。该算法利用残差结构将F1从0.799提高到0.9875;产品加速网络在不显著降低精度的情况下，将运行时间从0.025s减少到0.008s。在CD-KAGGLE数据集上的实验表明，本文设计的识别算法的准确率和鲁棒性都优于其他算法。
Fast recognition of cat and dog images based on network compression
Cat and dog recognition is a classic problem in the field of image recognition. This paper proposes a fast detection algorithm FAST-CD-Classification-Net for this problem. The algorithm improves F1 from 0.7299 to 0.9875 with the help of residual structure; The product acceleration network reduces the running time from 0.025s to 0.008s without significantly reducing the accuracy. Experiments on the data set CD-KAGGLE show that the accuracy and robustness of the recognition algorithm designed in this paper are better than other algorithms.
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