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The Influence of Image Degradation on Hyperspectral Image Classification

open access: yesRemote 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
doaj   +5 more sources

TUH-NAS: A Triple-Unit NAS Network for Hyperspectral Image Classification [PDF]

open access: yesSensors
Over 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
doaj   +2 more sources

Deep support vector machine for hyperspectral image classification

open access: yesPattern Recognition, 2020
To improve on the robustness of traditional machine learning approaches, emphasis has recently shifted to the integration of such methods with Deep Learning techniques.
Onuwa Okwuashi, Christopher E Ndehedehe
exaly   +2 more sources

HyperSFormer: A Transformer-Based End-to-End Hyperspectral Image Classification Method for Crop Classification

open access: yesRemote Sensing, 2023
Crop classification of large-scale agricultural land is crucial for crop monitoring and yield estimation. Hyperspectral image classification has proven to be an effective method for this task.
Jiaxing Xie   +9 more
doaj   +2 more sources

Enhanced Hyperspectral Image Classification Technique Using PCA-2D-CNN Algorithm and Null Spectrum Hyperpixel Features [PDF]

open access: yesSensors
With 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
doaj   +2 more sources

A Lightweight 1-D Convolution Augmented Transformer with Metric Learning for Hyperspectral Image Classification

open access: yesSensors, 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
doaj   +1 more source

Research and Application of Several Key Techniques in Hyperspectral Image Preprocessing

open access: yesFrontiers 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
doaj   +1 more source

Contrastive Learning Based on Transformer for Hyperspectral Image Classification

open access: yesApplied 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
doaj   +1 more source

Spectral-spatial multi-layer perceptron network for hyperspectral image land cover classification

open access: yesEuropean 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
doaj   +1 more source

Multi-scale guided feature extraction and classification algorithm for hyperspectral images

open access: yesScientific 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
doaj   +1 more source

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