Residual Spectral-Spatial Attention Network for Hyperspectral Image Classification
By Min Zhu, L. Jiao, Fang Liu, Shuyuan Yang, Jianing Wang. IEEE Transactions on Geoscience and Remote Sensing, 2021
438 citations recorded by the source corpus.
Subfields: Atmospheric Science, Media Technology
View Paper: https://www.semanticscholar.org/paper/651e0a0c23f68134603dc791f09492f59d0e194b
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Atmospheric Science
- Antonio J. Plaza
- Jocelyn Chanussot
- Qian Du
- Swalpa Kumar Roy
- Danfeng Hong
- Juan Mario Haut
- Jon Atli Benediktsson
- Lorenzo Bruzzone
In Media Technology
- Antonio J. Plaza
- Jocelyn Chanussot
- Swalpa Kumar Roy
- Danfeng Hong
- Qian Du
- Juan Mario Haut
- Behnood Rasti
- Jon Atli Benediktsson
Citations in the corpus
- Spectral–Spatial Morphological Attention Transformer for Hyperspectral Image Classification (2023, background): “Zhu et al. [36] incorporated other channel and spatial attention layers inside the SSRN architecture for extracting discriminative features.”
- Multimodal Fusion Transformer for Remote Sensing Image Classification (2022, background): “included another spatial and channel attention layer in the SSRN architecture to extract discriminative representation [40].”
- Attention-Based Adaptive Spectral–Spatial Kernel ResNet for Hyperspectral Image Classification (2020, background): “Recently, Zhu et al. [33] proposed RSSAN by introducing a spectral–spatial attention layer to SSRN.”