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The data of the second branch is constructed by resampling the generative network training method to improve the data quality. A bilateral\u2010branch network model is used to curb the risk of gradient explosion and to avoid over\u2010fitting and under\u2010fitting with the combined effect of different data branches. Meanwhile, Time\u2010supervised strategy is introduced to improve the model\u2032s operational efficiency and ability to cope with extreme conditions by supervising and collaboratively controlling of the bilateral\u2010branch generative network with time\u2010invariant parameters. Time supervised strategy could ensure the accuracy of the model while reducing the number of iterations. Experimental results on two publicly available datasets, CIFAR10 and CIFAR100, show that the proposed method effectively improves the performance of long\u2010tail data classification.<\/jats:p>","DOI":"10.1155\/2021\/8667868","type":"journal-article","created":{"date-parts":[[2021,11,2]],"date-time":"2021-11-02T23:50:07Z","timestamp":1635897007000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Classification of Long\u2010Tailed Data Based on Bilateral\u2010Branch Generative Network with Time\u2010Supervised Strategy"],"prefix":"10.1155","volume":"2021","author":[{"given":"Yalin","family":"Huang","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8213-0911","authenticated-orcid":false,"given":"Yan-Hui","family":"Zhu","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5780-2571","authenticated-orcid":false,"given":"Zeng","family":"Zhigao","sequence":"additional","affiliation":[]},{"given":"Yangkang","family":"Ou","sequence":"additional","affiliation":[]},{"given":"Lingwei","family":"Kong","sequence":"additional","affiliation":[]}],"member":"311","published-online":{"date-parts":[[2021,11,2]]},"reference":[{"key":"e_1_2_9_1_2","doi-asserted-by":"publisher","DOI":"10.1007\/s11263-015-0816-y"},{"key":"e_1_2_9_2_2","doi-asserted-by":"crossref","unstructured":"HeK. 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