Journal ArticleDOI
Computational intelligence in optical remote sensing image processing
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TLDR
An overview of the application of computational intelligence technologies in optical remote sensing image processing, including: 1) feature representation and selection; 2) classification and clustering; and 3) change detection are provided.About:
This article is published in Applied Soft Computing.The article was published on 2018-03-01. It has received 133 citations till now. The article focuses on the topics: Computational intelligence & Feature (computer vision).read more
Citations
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Journal ArticleDOI
Unsupervised Deep Change Vector Analysis for Multiple-Change Detection in VHR Images
TL;DR: A novel unsupervised context-sensitive framework—deep change vector analysis (DCVA)—for CD in multitemporal VHR images that exploit convolutional neural network (CNN) features is proposed and experimental results on mult itemporal data sets of Worldview-2, Pleiades, and Quickbird images confirm the effectiveness of the proposed method.
Journal ArticleDOI
Change Detection Based on Artificial Intelligence: State-of-the-Art and Challenges
Wenzhong Shi,Min Zhang,Min Zhang,Rui Zhang,Shanxiong Chen,Shanxiong Chen,Zhao Zhan,Zhao Zhan +7 more
TL;DR: This review focuses on the state-of-the-art methods, applications, and challenges of AI for change detection, and the commonly used networks in AI forchange detection are described.
Journal ArticleDOI
A Survey on Cooperative Co-Evolutionary Algorithms
TL;DR: A comprehensive survey of CCEAs, covering problem decomposition, collaborator selection, individual fitness evaluation, subproblem resource allocation, implementations, benchmark test problems, control parameters, theoretical analyses, and applications is presented.
Journal ArticleDOI
A Feature Difference Convolutional Neural Network-Based Change Detection Method
Min Zhang,Wenzhong Shi +1 more
TL;DR: A high-resolution RS image change detection approach based on a deep feature difference convolutional neural network (CNN) that achieves better performance compared with other classic approaches and has fewer missed detections and false alarms, proves that the proposed approach has strong robustness and generalization ability.
Journal ArticleDOI
Classification of Hyperspectral Image Based on Double-Branch Dual-Attention Mechanism Network
TL;DR: Wang et al. as mentioned in this paper proposed a double-branch dual-attention mechanism network (DBDA) for hyperspectral image classification, where two branches are designed to capture spectral and spatial features contained in HSI.
References
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Reducing the Dimensionality of Data with Neural Networks
TL;DR: In this article, an effective way of initializing the weights that allows deep autoencoder networks to learn low-dimensional codes that work much better than principal components analysis as a tool to reduce the dimensionality of data is described.
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Representation Learning: A Review and New Perspectives
TL;DR: Recent work in the area of unsupervised feature learning and deep learning is reviewed, covering advances in probabilistic models, autoencoders, manifold learning, and deep networks.
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Video Google: a text retrieval approach to object matching in videos
TL;DR: An approach to object and scene retrieval which searches for and localizes all the occurrences of a user outlined object in a video, represented by a set of viewpoint invariant region descriptors so that recognition can proceed successfully despite changes in viewpoint, illumination and partial occlusion.
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Data clustering: 50 years beyond K-means
TL;DR: A brief overview of clustering is provided, well known clustering methods are summarized, the major challenges and key issues in designing clustering algorithms are discussed, and some of the emerging and useful research directions are pointed out.
Journal ArticleDOI
Review Article Digital change detection techniques using remotely-sensed data
TL;DR: An evaluation of results indicates that various procedures of change detection produce different maps of change even in the same environment.