HIGHLIGHTS
- who: Peng Zeng and colleagues from the Hunan Institute of Land and Resources Planning, Changsha, China Faculty of Artificial Intelligence in Education, Central China Normal University, Wuhan, China have published the research: Exploiting Hierarchical Label Information in an Attention-Embedding, Multi-Task, Multi-Grained, Network for Scene Classification of Remote Sensing Imagery, in the Journal: (JOURNAL)
- what: In this paper to exploit label information the authors propose an attentionembedding multi-grained network (AEMMN) for remote sensing scene classification. To suppress the negative transfer feature learning-gradient backpropagation the model can achieve excellent caused by irrelevant . . .
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