Multiscale Progressive Complementary Fusion Network for Fine-Grained Visual Classification

In fine-grained visual classification(FGVC), small inter-class variations and large intra-class variations are always inherent attributes, so it is much more challenging than traditional classification tasks. Recent studies have mainly tackled this problem by employing attention mechanisms to locate...

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Veröffentlicht in:	IEEE access 2022, Vol.10, p.62800-62810
Hauptverfasser:	Lei, Jingsheng, Yang, Xinqi, Yang, Shengying
Format:	Artikel
Sprache:	eng
Schlagworte:	Annotations Classification Data integration Feature enhancement Feature extraction feature fusion feature suppression fine-grained visual classification Fuses progressive training Semantics Task analysis Training Visualization
Online-Zugang:	Volltext
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