Dictionary learning for fast classification based on soft-thresholding
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Malignant melanoma is the most deadly for of skin lesion. Early diagnosis is of critical importance to patient survival. Visual recognition algorithms could potentially be of great help for physicians in a computer assisted diagnosis system. Previous work ...
In this paper, we present a system for image replica detection. The technique is based on the extraction of 162 features corresponding to texture, colour and grey-level characteristics. These features are then weighted and statistically normalized. To impr ...
This thesis addresses text-independent speaker verification from a machine learning point of view. We use the machine learning framework to better define the problem and to develop new unbiased performance measures and statistical tests to compare objectiv ...
Categorization is one of the fundamental building blocks of cognitive systems. Object categorization has traditionally been addressed in the vision domain, even though cognitive agents are intrinsically multimodal. Indeed, biological systems combine severa ...
This paper addresses the issue of automatic classification of the six universal emotional categories (joy, surprise, fear, anger, disgust, sadness) in the case of static images. Appearance parameters are extracted by an active appearance model(AAM) represe ...
The inclusion of mental tasks transitions detection (MTTD) has proven a useful tool in guiding the transduction process of a BCI working under an asynchronous protocol. MTTD allows for the extraction of the signal's contextual information in order to infer ...
Machine Learning is a modern and actively developing field of computer science, devoted to extracting and estimating dependencies from empirical data. It combines such fields as statistics, optimization theory and artificial intelligence. In practical task ...
Melanoma is the most deadly skin cancer. Early diagnosis is a current challenge for clinicians. Current algorithms for skin lesions classification focus mostly on segmentation and feature extraction. This paper instead puts the emphasis on the learning pro ...
This paper proposes an algorithm for distributed classification, based on a SVM scheme. The contribution of each support vector is approximated by low complexity distributed thresholding over sub-dictionaries, whose union forms a redundant dictionary of at ...
Machine Learning is a modern and actively developing field of computer science, devoted to extracting and estimating dependencies from empirical data. It combines such fields as statistics, optimization theory and artificial intelligence. In practical task ...