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A common trend in machine learning and pattern classification research is the exploitation of massive amounts of information in order to achieve an increase in performance. In particular, learning from huge collections of data obtained from the web, and us ...
A common trend in machine learning and pattern classification research is the exploitation of massive amounts of information in order to achieve an increase in performance. In particular, learning from huge collections of data obtained from the web, and us ...
In many real world applications we do not have access to fully-labeled training data, but only to a list of possible labels. This is the case, e.g., when learning visual classifiers from images downloaded from the web, using just their text captions or tag ...
We consider the problem of classification of a pattern from multiple compressed observations that are collected in a sensor network. In particular, we exploit the properties of random projections in generic sensor devices and we take some first steps in in ...
The computing community has shown a significant interest for the analysis of social interactions in the last decade. Different aspects of social interactions have been studied such as dominance, emotions, conflicts, etc. However, the recognition of roles h ...
The level of dexterity of myoelectric hand prostheses depends to large extent on the feature representation and subsequent classification of surface electromyography signals. This work presents a comparison of various feature extraction and classification ...
Very often in change detection only few labels or even none are available. In order to perform change detection in these extreme scenarios, they can be considered as novelty detection problems, semi-supervised (SSND) if some labels are available otherwise ...
We propose a semiautomatic procedure to generate land cover maps from remote sensing images. The proposed algorithm starts by building a hierarchical clustering tree, and exploits the most coherent pixels with respect to the available class information. Fo ...
Neurological patients with impaired upper limbs often receive arm therapy to restore or relearn lost motor functions. During the last years robotic devices were developed to assist the patient during the training. In daily life the diversity of movements i ...
Training Support Vector Machines (SVMs) to predict drugs concentrations is often difficult because of the high level of noise in the training data, due to various kinds of measurement errors. We apply RANdom SAmple Consensus (RANSAC) algorithm in this pape ...
