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Accurate land use/cover (LUC) classifications from satellite imagery are very important for eco-environment monitoring, land use planning and climatic change detection. Traditional statistical classifiers such as minimum distance (MD) have been used to extract LUC classifications in urban areas, but these classifiers rely on assumptions that may limit their utilities for many datasets. On the contrary,...
wireless capsule endoscopy (WCE) is an important device to detect abnormalities in small intestine. Despite emerging technologies, reviewing capsule endoscopic video is a labor intensive task and very time consuming. Computational tools which automatically detect informative frames and tag abnormal conditions such as bleeding, ulcer or tumor will dramatically reduce the clinician's effort. In this...
This paper presents recently introduced learning algorithm called extreme learning machine (ELM) for single-hidden layer feed-forward neural-networks (SLFNs) which randomly chooses hidden nodes and analytically determines the output weights of SLFNs. The ELM avoids problems like local minima, improper learning rate and over fitting commonly faced by iterative learning methods and completes the training...
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