Results 31 to 40 of about 112,589 (145)
Remote Sensing, 2020 In this paper, superpixel features and extended multi-attribute profiles (EMAPs) are embedded in a multiple kernel learning framework to simultaneously exploit the local and multiscale information in both spatial and spectral dimensions for hyperspectral
Lei Pan, Chengxun He, Yang Xiang, Le Sun
doaj +1 more source
Remote Sensing, 2023 Convolutional neural networks (CNNs) and graph convolutional networks (GCNs) have led to promising advancements in hyperspectral image (HSI) classification; however, traditional CNNs with fixed square convolution kernels are insufficiently flexible to ...
Junru Yin +6 more
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Advanced Intelligent Systems, Volume 8, Issue 7, July 2026.Four decades of retinal vessel segmentation research (1982–2025) are synthesized, spanning classical image processing, machine learning, and deep learning paradigms. A meta‐analysis of 428 studies establishes a unified taxonomy and highlights performance trends, generalization capabilities, and clinical relevance.
Avinash Bansal +6 more
wiley +1 more source
, 2022 In this paper, a hand-crafted spectral-spatial feature extraction (SEA-FE) method for classification of hyperspectral images (HSIs) is proposed to improve the classification performance, especially in the limited labelled training samples.
Seyyed Ali Ahmadi, Nasser Mehrshad
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Coarse-grained modeling of multiscale diffusions : the p-variation estimates [PDF]
, 2010 We study the problem of estimating parameters of the limiting equation of a multiscale diffusion in the case of averaging and homogenization, given data from the corresponding multiscale system.
Papavasiliou, Anastasia +1 more
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A Bridge Transformer Network With Deep Graph Convolution for Hyperspectral Image Classification
CAAI Transactions on Intelligence Technology, Volume 11, Issue 2, Page 464-482, April 2026.ABSTRACT Transformers have been widely applied to hyperspectral image classification, leveraging their self‐attention mechanism for powerful global modelling. However, two key challenges remain as follows: excessive memory and computational costs from calculating correlations between all tokens (especially as image size or spectral bands increase) and ...
Yuquan Gan +5 more
wiley +1 more source
Electronics Letters, Volume 62, Issue 1, January/December 2026.This letter presents an unsupervised stereoscopic saliency detection method for rail surface defects that integrates global low‐rank reconstruction with depth outlier analysis. A binocular line‐scanning system simultaneously acquires RGB images and depth maps, with a Global Low‐Rank Nonnegative Reconstruction (GLRNNR) algorithm extracting 2D saliency ...
Zhiwen Xiong, Yuanchun Li
wiley +1 more source
Remote Sensing, 2019 Automatic building extraction using a single data type, either 2D remotely-sensed images or light detection and ranging 3D point clouds, remains insufficient to accurately delineate building outlines for automatic mapping, despite active research in this
Haiqing He +5 more
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IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2022 Weakly supervised semantic segmentation (WSSS) methods based on image-level labels can relieve the tedious pixel-level annotation burden, and these methods are mainly based on class activation maps (CAMs).
Xin Yan +4 more
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IET Image Processing, Volume 20, Issue 1, January/December 2026.This study proposes a Gated and Cross‐Dynamically Enhanced Network (GCD‐Net) for accurate extraction of offshore raft aquaculture from Sentinel‐2 imagery. GCD‐Net integrates novel gated residual blocks, cross‐guided attention, and dynamic attention ASPP modules to enhance feature representation and boundary precision.
Yu Wang +4 more
wiley +1 more source