Contextual classification of multispectral image data: Approximate algorithm [PDF]
, 1980 An approximation to a classification algorithm incorporating spatial context information in a general, statistical manner is presented which is computationally less intensive.
Tilton, J. C.
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Automatic joint segmentation and classification of breast ultrasound images via multi-task learning with object contextual attention [PDF]
Frontiers in OncologyThe segmentation and classification of breast ultrasound (BUS) images are crucial for the early diagnosis of breast cancer and remain a key focus in BUS image processing.
Yaling Lu +3 more
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Remote Sensing, 2022 In recent years, convolutional neural networks (CNNs) have been widely used in hyperspectral image (HSI) classification. However, feature extraction on hyperspectral data still faces numerous challenges.
Jun Sun +6 more
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Remote Sensing Image Change Detection Method Based on DBN and Object Fusion [PDF]
Jisuanji gongcheng, 2018 In high-resolution optical remote sensing image change detection,most of the object-oriented method can only use simple features combination to get the object features,which cannot implement design and characteristic extraction for high-level features ...
DOU Fangzheng,SUN Hanchang,SUN Xian,DIAO Wenhui,FU Kun
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CONTEXTUAL LAND USE CLASSIFICATION: HOW DETAILED CAN THE CLASS STRUCTURE BE? [PDF]
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2016 The goal of this paper is to investigate the maximum level of semantic resolution that can be achieved in an automated land use change detection process based on mono-temporal, multi-spectral, high-resolution aerial image data.
L. Albert, F. Rottensteiner, C. Heipke
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Contextual classification and segmentation of textured images [PDF]
International Conference on Acoustics, Speech, and Signal Processing, 2002 An algorithm which combines the merits of statistical classification- and estimation-theory-based approaches is proposed for textured image segmentation. The texture regions are modeled by noncausal Gaussian Markov random fields (GMRF). The algorithm is comprised of two stages.
P.W. Fung, G. Grebbin, Y. Attikiouzel
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CMLBPIncoherent: a New Contextual Image Descriptor for Scene Classification
Anais do 14º Simpósio Brasileiro de Automação Inteligente, 2019 Matheus Vieira Lessa Ribeiro +1 more
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Land Cover Mapping with Higher Order Graph-Based Co-Occurrence Model
Remote Sensing, 2018 Deep learning has become a standard processing procedure in land cover mapping for remote sensing images. Instead of relying on hand-crafted features, deep learning algorithms, such as Convolutional Neural Networks (CNN) can automatically generate ...
Wenzhi Zhao +3 more
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RULE-BASED CLASSIFICATION OF A HYPERSPECTRAL IMAGE USING MSSC HIERARCHICAL SEGMENTATION [PDF]
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2013 The Hierarchical SEGmentation (HSEG) algorithm, which combines region object finding with region object clustering, has given good performances for hyperspectral image analysis.
D. Akbari, A. R. Safari
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Crop conditional Convolutional Neural Networks for massive multi-crop plant disease classification over cell phone acquired images taken on real field conditions [PDF]
, 2019 Convolutional Neural Networks (CNN) have demonstrated their capabilities on the agronomical field, especially for plant visual symptoms assessment.
Alvarez-Gila, Aitor +5 more
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