S³Net: Spectral–Spatial–Semantic Network for Hyperspectral Image Classification With the Multiway Attention Mechanism
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Transactions on Geoscience and Remote Sensing"
DOI: 10.1109/tgrs.2021.3067356
Abstract: In hyperspectral image (HSI) classification, it is a great challenge on how to extract key informative spectral–spatial features efficiently and suppress useless features from abundant spectral–spatial information. In this article, inspired by the attention mechanism… read more here.
Keywords: attention mechanism; spatial semantic; attention; multiway attention ... See more keywords
Unsupervised Spectral-Spatial Semantic Feature Learning for Hyperspectral Image Classification
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Transactions on Geoscience and Remote Sensing"
DOI: 10.1109/tgrs.2022.3159789
Abstract: Can we automatically learn meaningful semantic feature representations when training labels are absent? Several recent unsupervised deep learning approaches have attempted to tackle this problem by solving the data reconstruction task. However, these methods can… read more here.
Keywords: classification; spectral spatial; feature; semantic feature ... See more keywords
SST: Spatial and Semantic Transformers for Multi-Label Image Recognition
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Transactions on Image Processing"
DOI: 10.1109/tip.2022.3148867
Abstract: Multi-label image recognition has attracted considerable research attention and achieved great success in recent years. Capturing label correlations is an effective manner to advance the performance of multi-label image recognition. Two types of label correlations… read more here.
Keywords: label image; multi label; spatial semantic; image recognition ... See more keywords
Audio-Visual Event Localization by Learning Spatial and Semantic Co-Attention
Sign Up to like & getrecommendations! Published in 2023 at "IEEE Transactions on Multimedia"
DOI: 10.1109/tmm.2021.3127029
Abstract: This work aims to temporally localize events that are both audible and visible in video. Previous methods mainly focused on temporal modeling of events with simple fusion of audio and visual features. In natural scenes,… read more here.
Keywords: attention; audio visual; spatial semantic; event localization ... See more keywords