Vincenzo Piuri

TL;DR: Two fault detection schemes are presented: the first is a redundancy-based scheme while the second uses an error detecting code, which is a novel scheme which leads to very efficient and high coverage fault detection.

TL;DR: A new public dataset of blood samples is proposed, specifically designed for the evaluation and the comparison of algorithms for segmentation and classification, to offer a new test tool to the image processing and pattern matching communities.

TL;DR: Deep-ECG extracts significant features from one or more leads using a deep CNN and compares biometric templates by computing simple and fast distance functions, obtaining remarkable accuracy for identification, verification and periodic re-authentication.

TL;DR: An innovative, system-level, modular perspective on creating and managing fault tolerance in Clouds is introduced and a comprehensive high-level approach to shading the implementation details of the fault tolerance techniques to application developers and users by means of a dedicated service layer is proposed.

TL;DR: This paper presents a methodology to achieve an automated detection and classification of leucocytes by microscope color images and firstly individuates in the blood image the leucocyte from the others blood cells, then it extracts morphological indexes and finally it classifies the leukocytes by a neural classifier in Basophil, Eosinophils, Lymphocyte, Monocyte and Neutrophil.