Video Captioning With Adaptive Attention and Mixed Loss Optimization
Sign Up to like & getrecommendations! Published in 2019 at "IEEE Access"
DOI: 10.1109/access.2019.2942000
Abstract: The attention mechanism and sequence-to-sequence framework have shown promising advancements in the temporal task of video captioning. However, imposing the attention mechanism on non-visual words, such as “of” and “the”, may mislead the decoder and… read more here.
Keywords: attention; loss; adaptive attention; video captioning ... See more keywords
Mixed Loss Graph Attention Network for Few-Shot SAR Target Classification
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Transactions on Geoscience and Remote Sensing"
DOI: 10.1109/tgrs.2021.3124336
Abstract: Restricted by the observation condition, synthetic aperture radar (SAR) automatic target classification based on deep learning usually suffers from insufficient training samples. To tackle this problem, a novel few-shot learning (FSL) framework for SAR target… read more here.
Keywords: network; classification; target classification; mixed loss ... See more keywords