Learning geometric Jensen-Shannon divergence for tiny object detection in remote sensing images.

Ni, Shuyan; Lin, Cunbao; Wang, Haining; Li, Yang; Liao, Yurong; Li, Na

Ni, Shuyan; Lin, Cunbao; Wang, Haining; Li, Yang; Liao, Yurong; Li, Na.

Afiliación

Ni S; Department of Electronic and Optical Engineering, Space Engineering University, Beijing, China.
Lin C; Department of Electronic and Optical Engineering, Space Engineering University, Beijing, China.
Wang H; Institute of Artificial Intelligence, Beihang University, Beijing, China.
Li Y; Aerospace Optical-Microwave Integrated Precision Intelligent Sensing, Key Laboratory of Ministry of Industry and Information Technology, Beihang University, Beijing, China.
Liao Y; Department of Electronic and Optical Engineering, Space Engineering University, Beijing, China.
Li N; Department of Electronic and Optical Engineering, Space Engineering University, Beijing, China.

Front Neurorobot ; 17: 1273251, 2023.

Article en En | MEDLINE | ID: mdl-38023452

Palabras clave

Gaussian distribution; Jensen-Shannon divergence; deep learning; remote sensing images; tiny object detection

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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: Front Neurorobot Año: 2023 Tipo del documento: Article País de afiliación: China Pais de publicación: Suiza

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