The SISSI project is a three-year project focusing on the design and development of a multi-sensor portal for train safety. SISSI is funded by the Region of Tuscany and MICC contributes its expertise in video and image analysis to the project in order to analyze passing cargo trains and measure and detect critical situations.
The SISSI project involves the exploitation of high speed sensors, both linear and matrix, in the visible spectrum and thermal spectrum in order to measure critical factors in passing cargo trains.View Project
In this research project we collaborated with Cynny, a start-up based in Florence and Silicon Valley to develop innovative low-footprint convolutional neural network based object detectors, that can be efficiently executed on mobile devices. In such environments, battery and computational resources are very limited, requiring a specialized and efficient network architecture. We produced an effective and efficient system prototype that can perform object detections on typical mobile CPUs in hundreds of milliseconds.
Images in social networks share different destinies: some are going to become popular while others are going to be completely unnoticed. In this paper we propose to use visual sentiment features together with three novel context features to predict a concise popularity score of social images. Experiments on large scale datasets show the benefits of the proposed features. We report a qualitative analysis of which sentiments seem to be related to good or poor popularity.View Project