Exploiting ConvNet Diversity for Flooding Identification
語義分割洪水區域。網絡
空洞卷積和反捲積組合，結果再用svm學習如何組合，能得到更好的效果。學習
直接對不一樣網絡的結果進行投票會獲得更差的結果。設計
消融研究（Ablation Study）：相似控制變量法，就對那些可能影響網絡精度的參數進行不一樣組合，從而獲得最好的設計io
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相關文章
- 1. DIVERSITY REGULARIZED METRIC LEARNING FOR PERSON RE-IDENTIFICATION（ICIP2016）
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