Vitoantonio Bevilacqua

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Face recognition from an image or video sequences is emerging as an active research area with numerous commercial and law enforcement applications. In this paper different Pseudo 2-dimension Hidden Markov Models (HMMs) are introduced for a face recognition showing performances reasonably fast for binary images. The proposed P2-DHMMs aremade up of five(More)
DNA microarray data are used to identify genes which could be considered prognostic markers. However, due to the limited sample size of each study, the signatures are unstable in terms of the composing genes and may be limited in terms of performances. It is therefore of great interest to integrate different studies, thus increasing sample size. In the(More)
This paper presents a novel approach to artificial neural network (ANN) topology optimisation that uses multi-objective genetic algorithm in order to find the best network configuration for the Wisconsin breast cancer database (WBCD) classification problem. The WBCD [Mangasarian, OL., et al., 1995][Mangasarian, OL., et al.][Wolberg, WH., et al., 1995] is a(More)
For the purposes of this research, the optimal MLP neural network topology has been designed and tested by means the specific genetic algorithm multi-objective Pareto-Based. The objective of the research is to predict the trend of the exchange rate Euro/USD up to three days ahead of last data available. The variable of output of the ANN designed is then the(More)
Microarrays allow biologists to better understand the interactions between diverse pathologic states at the gene level. However, the amount of data generated by these tools becomes problematic. New techniques are then needed in order to extract valuable information about gene activity in sensitive processes like tumor cells proliferation and metastasis(More)
This paper describes a comparative study between an Artificial Neural Network (ANN) and a geometric technique to detect for biometric applications,the bifurcation points of blood vessels in the retinal fundus. The first step is an image preprocessing phase to extract retina blood vessels. The contrast of the blood vessels from the retinal image background(More)
This paper presents a hierarchical classification system based on the kNearest Neighbors (kNN) classifier for classification of ten different classes of Malignant and Benign skin lesions from color image data. Our key contribution is to focus on the ten most common classes of skin lesions. There are five malignant: Actinic Keratosis (AK), Basal Cell(More)
Microarrays allow biologists to better understand the interactions between diverse pathologic states at the gene level. However, the amount of data generated by these tools becomes problematic. New techniques are then needed in order to extract valuable information about gene activity in sensitive processes like tumor cells proliferation and metastasis(More)