Results 21 to 30 of about 12,889,375 (285)
Nested Transformers for Hyperspectral Image Classification
Journal of Sensors, 2022 Substantial deep learning methods have been utilized for hyperspectral image (HSI) classification recently. Vision Transformer (ViT) is skilled in modeling the overall structure of images and has been introduced to HSI classification task. However, the fixed patch division operation in ViT may lead to insufficient feature extraction, especially the ...
Zitong Zhang 0001 +3 more
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Customizing kernel functions for SVM-based hyperspectral image classification [PDF]
, 2008 Previous research applying kernel methods such as support vector machines (SVMs) to hyperspectral image classification has achieved performance competitive with the best available algorithms.
Damper, R. I. +7 more
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Delving Into Classifying Hyperspectral Images via Graphical Adversarial Learning
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2020 Recent remote sensing literature has seen generative adversarial network (GAN)-based models developed for hyperspectral image classification, especially in a spatiospectral manner.
Guangxing Wang, Peng Ren
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Triplet-Watershed for Hyperspectral Image Classification [PDF]
IEEE Transactions on Geoscience and Remote Sensing, 2022 Hyperspectral images (HSI) consist of rich spatial and spectral information, which can potentially be used for several applications. However, noise, band correlations and high dimensionality restrict the applicability of such data. This is recently addressed using creative deep learning network architectures such as ResNet, SSRN, and A2S2K.
Aditya Challa +3 more
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Remote 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
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Mahalanobis kernel for the classification of hyperspectral images [PDF]
2010 IEEE International Geoscience and Remote Sensing Symposium, 2010 The definition of the Mahalanobis kernel for the classification of hyperspectral remote sensing images is addressed. Class specific covariance matrices are regularized by a probabilistic model which is based on the data living in a subspace spanned by the p first principal components.
Fauvel, Mathieu +3 more
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Hyperspectral Image Database Query Based on Big Data Analysis Technology [PDF]
E3S Web of Conferences, 2021 In this paper, we extract spectral image features from a hyperspectral image database, and use big data technology to classify spectra hierarchically, to achieve the purpose of efficient database matching.
Qi Beixun
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Hyperspectral Image Classification Scheme with Boundary Constrain Label Smoothing Based on Block Neighbor [PDF]
Jisuanji gongcheng, 2017 In order to improve the accuracy of hyperspectral image classification,combined with spectral information,neighborhood information and boundary information,this paper proposes a hyperspectral image classification scheme.The method takes the Local Fisher ...
CHEN Shanxue,GUI Chengming,WANG Yining
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IEEE Access, 2020 In order to improve the classification of hyperspectral image(HSI), we propose a novel hyperspectral image classification method based on the comprehensive evaluation model of extreme learning machine(ELM) with the cumulative variation weights(CVW ...
Yuping Yin, Lin Wei
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Supervised hyperspectral image classification with rejection
2015 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), 2015 Hyperspectral image classification is a challenging problem as obtaining complete and representative training sets is costly, pixels can belong to unknown classes, and it is generally an ill-posed problem. The need to achieve high classification accuracy may surpass the need to classify the entire image.
Filipe Condessa +2 more
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