Results 31 to 40 of about 118,760 (177)
Research on land use classification of hyperspectral images based on multiscale superpixels
Mathematical Biosciences and Engineering, 2020 With the rapid development of remote sensing technology, research on land use classification methods based on hyperspectral remote sensing images has attracted widespread attention. Existing land-use classification studies mostly use the average filtering method at a single scale for spectral image processing. These methods cannot accurately filter the
Hua Wang +4 more
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, 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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Superpixel labeling for medical image segmentation [PDF]
, 2023 openNowadays, most methods for image segmentation consider images in a pixel- wise manner, which is a huge job and also time-consuming. On the other hand, superpixel labeling can make the segmentation task easier in some aspects. First, superpixels carry
REZAEI, SOMAYEH
core
SGML: A Symmetric Graph Metric Learning Framework for Efficient Hyperspectral Image Classification
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2022 Recently, the semi-supervised graph convolutional network (SSGCN) has been verified effective for hyperspectral image (HSI) classification. However, constrained by the limited training data and spectral uncertainty, the classification performance is ...
Yunsong Li +5 more
doaj +1 more source
Efficient Multiscale Object-based Superpixel Framework
Journal of the Brazilian Computer SocietySuperpixel segmentation can be used as an intermediary step in many applications, often to improve object delineation and reduce computer workload. However, classical methods do not incorporate information about the desired object. Deep-learning-based approaches consider object information, but their delineation performance depends on data annotation ...
Felipe C. Belém +4 more
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IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2021 Although deep learning-based methods have been successfully applied to polarimetric synthetic aperture radar (PolSAR) image classification tasks, most of the available techniques are not suitable to deal with PolSAR data on irregular domains, e.g ...
Shijie Ren, Feng Zhou
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Superpixel-based spatial amplitude and phase modulation using a digital micromirror device [PDF]
, 2014 We present a superpixel method for full spatial phase and amplitude control of a light beam using a digital micromirror device (DMD) combined with a spatial filter.
SA Goorden (21996356) +2 more
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Remote Sensing in Ecology and Conservation, EarlyView.High‐resolution visible‐light imagery from low‐altitude unmanned aerial vehicles, combined with superpixel segmentation and a Random Forest classifier, provides an efficient and scalable framework for mapping and monitoring crustose coralline algae and reef habitats.
Po‐Chien Lin +2 more
wiley +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