Fuzzy sets and fuzzy logic: theory and applications
Fuzzy sets and fuzzy logic: theory and applications
Text Classification from Labeled and Unlabeled Documents using EM
Machine Learning - Special issue on information retrieval
Training Algorithm with Incomplete Data for Feed-ForwardNeural Networks
Neural Processing Letters
Using Unlabelled Data to Train a Multilayer Perceptron
Neural Processing Letters
Pattern Classification (2nd Edition)
Pattern Classification (2nd Edition)
Remote Sensing Digital Image Analysis: An Introduction
Remote Sensing Digital Image Analysis: An Introduction
Feature-based approach to semi-supervised similarity learning
Pattern Recognition
ICCTA '07 Proceedings of the International Conference on Computing: Theory and Applications
IEEE Transactions on Image Processing
Image change detection algorithms: a systematic survey
IEEE Transactions on Image Processing
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A context-sensitive change-detection technique based on semi-supervised learning with multilayer perceptron is proposed here. In order to take contextual information into account, input patterns are generated considering each pixel of the difference image along with its neighboring pixels. A heuristic technique is suggested to identify a few initial labeled patterns without using ground truth information. The network is initially trained using these labeled data. The unlabeled patterns are iteratively processed by the already trained perceptron to obtain a soft class label. Experimental results, carried out on two multispectral and multitemporal remote sensing images, confirm the effectiveness of the proposed approach.