Sergio Decherchi

Learn More
Providing a satisfactory visual experience is one of the main goals for present-day electronic multi-media devices. All the enabling technologies for storage, transmission, compression, rendering should preserve, and possibly enhance, the quality of the video signal; to do so, quality control mechanisms are required. These mechanisms rely on systems that(More)
In the last decades digital forensics has become a prominent activity in modern investigations. Seized digital devices can provide precious information and evidences about facts and/or individuals on which the investigational activity is performed. Due to the complexity of this inquiring activity and to the large amount of the data to be analyzed, the(More)
—Information Retrieval is a well established inter-disciplinary topic in which machine learning, computational linguistic, computer programming and data mining merge together. SLAIR stands for SeaLab Advanced Information Retrieval and is an efficient software architecture that embeds these issues in a unique framework. SLAIR is expandable both from the data(More)
Text-mining methods have become a key feature for homeland-security technologies, as they can help explore effectively increasing masses of digital documents in the search for relevant information. This research presents a model for document clustering that arranges unstructured documents into content-based homogeneous groups. The overall paradigm is hybrid(More)
We present a general, robust, and efficient ray-casting-based approach to triangulating complex manifold surfaces arising in the nano-bioscience field. This feature is inserted in a more extended framework that: i) builds the molecular surface of nanometric systems according to several existing definitions, ii) can import external meshes, iii) performs(More)
A crucial issue in designing learning machines is to select the correct model parameters. When the number of available samples is small, theoretical sample-based generalization bounds can prove effective, provided that they are tight and track the validation error correctly. The maximal discrepancy (MD) approach is a very promising technique for model(More)