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The work presented in this article consists in evaluating the contribution of the use of a texture-color combination in forest mapping. We transform a Spot image into different color spaces, then we extract nine parameters using Laws filter. The resulting set of parameters is reduced using MIFS algorithm based on mutual information. The results are promising and give satisfying classification results.
Machine learning is a branch of artificial intelligence that employs a variety of statistical, probabilistic and optimization techniques that allows computers to “learn” from past examples and to detect hard-to-discern patterns from large, noisy or complex data sets. As a result, machine learning is frequently used in cancer diagnosis and detection. In this paper, support vector machines, K-nearest...
In this paper we discuss a new approach for the detection of clustered microcalcifications (MCs) in mammograms. MCs are an important early sign of breast cancer in women. Their accurate detection is a key issue in computer aided detection scheme. To improve the performance of detection, we propose a Bagging and Boosting based twin support vector machine (BB-TWSVM) to detect MCs. The algorithm is composed...
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