In this thesis, it will be presented a set of computer vision algorithms mainly devoted to monitor the evolution of the content inside an ice-creams freezer for commercial purposes. In our work we have been asked to address ...

Al giorno d’oggi sono stati creati numerosi strumenti destinati ad aiutare i biologi nella loro attività di ricerca di fenomeni non ancora compresi. Essi sfruttano la grande mole di dati condivisi nella comunità scientifica. Uno ...

Verb Sense Disambiguation is a well known task in NLP, the aim is to find the correct sense of a verb in a sentence. Recently, this problem has been extended in multimodal scenario, by exploiting both textual and visual ...

Graphs and networks are everywhere, from social networks to the World Wide Web. Since the last decade, massive graphs has become the center attention of an intense research activity, both industrial and academic research ...

In this document, we present an object detection system for italian documents. Unlike similar systems which use a single deep-learning solution, this system employs different solutions for a fast and accurated detection. ...

In the last few years, autonomous driving has become a major topic in both car industry and academia. Many challenging problems remain to be solved, however, in order for autonomous cars to be on the market. In this thesis, ...

In this thesis we have studied how a technique based on how game theory can improve classification results obtained with a deep learning module. In order to get this improvement we have applied this method to the music ...

In this thesis, we present new schemes which leverage a constrained clustering method to solve several computer vision tasks ranging from image retrieval, image segmentation and co-segmentation, to person re-identification. ...

Recently, classical kernel methods have been extended by the introduction of suitable tensor kernels so to promote sparsity in the solution of the underlying regression problem. Indeed, they solve an lp-norm regularization ...

Context matters! Nevertheless, there has not been much research in exploiting contextual information in deep neural networks. For the most part, the entire usage of contextual information has been limited to recurrent ...