The Influence of Image Degradation on Hyperspectral Image Classification
Remote Sensing, 2022 Recent advances in hyperspectral remote sensing techniques, especially in the hyperspectral image classification techniques, have provided efficient support for recognizing and analyzing ground objects.
Congyu Li +3 more
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TUH-NAS: A Triple-Unit NAS Network for Hyperspectral Image Classification [PDF]
SensorsOver the last few years, neural architecture search (NAS) technology has achieved good results in hyperspectral image classification. Nevertheless, existing NAS-based classification methods have not specifically focused on the complex connection between ...
Feng Chen, Baishun Su, Zongpu Jia
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SSATNet: Spectral-spatial attention transformer for hyperspectral corn image classification
Frontiers in Plant ScienceHyperspectral images are rich in spectral and spatial information, providing a detailed and comprehensive description of objects, which makes hyperspectral image analysis technology essential in intelligent agriculture.
Bin Wang +7 more
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Synergistic 2D/3D Convolutional Neural Network for Hyperspectral Image Classification
Remote Sensing, 2020 Accurate hyperspectral image classification has been an important yet challenging task for years. With the recent success of deep learning in various tasks, 2-dimensional (2D)/3-dimensional (3D) convolutional neural networks (CNNs) have been exploited to
Xiaofei Yang +6 more
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Enhanced Hyperspectral Image Classification Technique Using PCA-2D-CNN Algorithm and Null Spectrum Hyperpixel Features [PDF]
SensorsWith the increasing availability of high-dimensional hyperspectral data from modern remote sensing platforms, accurate and efficient classification methods are urgently needed to overcome challenges such as spectral redundancy, spatial variability, and ...
Haitao Liu, Weihong Bi, Neelam Mughees
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Sensors, 2021 Hyperspectral image (HSI) classification is the subject of intense research in remote sensing. The tremendous success of deep learning in computer vision has recently sparked the interest in applying deep learning in hyperspectral image classification ...
Xiang Hu +4 more
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Contrastive Learning Based on Transformer for Hyperspectral Image Classification
Applied Sciences, 2021 Recently, deep learning has achieved breakthroughs in hyperspectral image (HSI) classification. Deep-learning-based classifiers require a large number of labeled samples for training to provide excellent performance.
Xiang Hu +4 more
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Research and Application of Several Key Techniques in Hyperspectral Image Preprocessing
Frontiers in Plant Science, 2021 This paper focuses on image segmentation, image correction and spatial-spectral dimensional denoising of images in hyperspectral image preprocessing to improve the classification accuracy of hyperspectral images.
Yu-hang Li +15 more
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Spectral-spatial multi-layer perceptron network for hyperspectral image land cover classification
European Journal of Remote Sensing, 2022 This paper proposes a novel spectral-spatial multi-layer perceptron network for hyperspectral image land cover classification. Current deep learning-based methods have limitations in spectral and spatial feature representation of hyperspectral images ...
Xiong Tan, Zhixiang Xue
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Multi-scale guided feature extraction and classification algorithm for hyperspectral images
Scientific Reports, 2021 To solve the problem that the traditional hyperspectral image classification method cannot effectively distinguish the boundary of objects with a single scale feature, which leads to low classification accuracy, this paper introduces the idea of guided ...
Shiqi Huang +3 more
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