Andrea Pennisi

In this paper, we propose a real-time multi-class detection system for the NAO V6 robot in the context of RoboCup SPL (Standard Platform League) using state-of-the-art structural pruning techniques on neural networks derived from YOLOv7-tiny. Our approach combines structural pruning and fine-tuning, to obtain a pruned network that maintains high ac...

The process of identifying obligations in a legal text is not a straightforward task, because not only are the documents long, but the sentences therein are long as well. As a result of long elements in the text, law is more difficult to interpret (Coupette et al., 2021). Moreover, the identification of obligations relies not only on the clarity an...

In this paper, we propose a real-time multi-class detection system for the NAO V6 robot in the context of RoboCup SPL (Stan-dard Platform League) using state-of-the-art structural pruning techniques on neural networks derived from YOLOv7-tiny. Our approach combines structural pruning and fine-tuning, to obtain a pruned network that maintains high a...

RoboCup is an International robotics initiative whose aim is to promote robotics and AI research. RoboCup's long-term goal is to create a fully autonomous humanoid robot team capable of competing and winning a soccer game against the human World champion team, in compliance with the official rules of FIFA, by 2050. In this paper, we describe a two-...

This technical report describes a modular and extensible architecture for computing visual statistics in RoboCup SPL (MARIO), presented during the SPL Open Research Challenge at RoboCup 2022, held in Bangkok (Thailand). MARIO is an open-source, ready-to-use software application whose final goal is to contribute to the growth of the RoboCup SPL comm...

Melanoma is the deadliest form of skin cancer. Early diagnosis of malignant lesions is crucial for reducing mortality. The use of deep learning techniques on dermoscopic images can help in keeping track of the change over time in the appearance of the lesion, which is an important factor for detecting malignant lesions. In this paper, we present a...

Oral squamous cell carcinoma is the most common oral cancer. In this paper, we present a performance analysis of four different deep learning-based pixel-wise methods for lesion segmentation on oral carcinoma images. Two diverse image datasets, one for training and another one for testing, are used to generate and evaluate the models used for segme...

Multi-Object Tracking (MOT) in airborne videos is a challenging problem due to the uncertain airborne vehicle motion, vibrations of the mounted camera, unreliable detections, changes of size, appearance and motion of the moving objects and occlusions caused by the interaction between moving and static objects in the scene. To deal with these proble...

Multi-object tracking (MOT) in airborne videos is a challenging problem due to the uncertain airborne vehicle motion, vibrations of the mounted camera, unreliable detections, size, appearance and motion of the moving objects as well as occlusions due to the interaction between the moving objects and with other static objects in the scene.To deal wi...

Melanoma is one of the deadliest form of cancer with an increasing incidence rate. The development of automatic diagnostic tools for the early detection of skin cancer lesions in dermoscopic images can help to reduce melanoma-induced mortality. In this paper, we present an automatic method for skin lesion image segmentation based on a deep learning...

Background subtraction is a widely used technique for detecting moving objects in image sequences. Very often background subtraction approaches assume the availability of one or more clear (i.e., without foreground objects) frames at the beginning of the sequence in input. However, this assumption is not always true, especially when dealing with dy...

Automatic surveillance systems for the maritime domain are becoming more and more important due to a constant increase of naval traffic and to the simultaneous reduction of crews on decks. However, available technology still provides only a limited support to this kind of applications. In this paper, a modular system for intelligent maritime survei...

Developing automatic diagnostic tools for the early detection of skin cancer lesions in dermoscopic images can help to reduce melanoma-induced mortality. Image segmentation is a key step in the automated skin lesion diagnosis pipeline. In this paper, a fast and fully-automatic algorithm for skin lesion segmentation in dermoscopic images is presente...

Automatically detecting events in crowded scenes is a challenging task in Computer Vision. A number of offline approaches have been proposed for solving the problem of crowd behavior detection, however the offline assumption limits their application in real-world video surveillance systems. In this paper, we propose an online and real-time method f...

Background subtraction is a widely used technique for detecting moving objects in image sequences. Very often background subtraction approaches assume the availability of one or more clear frames (i.e., without foreground objects) at the beginning of the image sequence in input. This strong assumption is not always correct, especially when dealing...

Automatic surveillance of public areas, such as airports, train stations, and shopping malls, requires the capacity of detecting and recognizing possible abnormal situations in populated environments. In this book chapter, an architecture for intelligent surveillance in indoor public spaces, based on an integration of interactive and non-interactiv...

Monitoring of populated indoor environments is crucial for the surveillance of public spaces like airports or embassies, where the behavior of people may be relevant in order to determine abnormal situations. In this paper, a surveillance system based on an integration of interactive and non-interactive heterogeneous sensors is described. As a diff...

Maritime environment represents a challenging scenario for automatic video surveillance due to the complexity of the observed scene: waves on the water surface, boat wakes, and weather issues contribute to generate a highly dynamic background. Moreover, an appropriate background model has to deal with gradual and sudden illumination changes, camera...

In this paper an open source software for monitoring hu-manoid soccer robot behaviours is presented. The software is part of an easy to set up system, conceived for registering ground truth data that can be used for evaluating and testing methods such as robot co-ordination and localization. The hardware architecture of the system is designed for u...

Camera calibration is a necessary step in order to develop applications that need to establish a relationship between image pixels and real world points. The goal of camera calibration is to estimate the extrinsic and intrinsic camera parameters. Usually, for non-zooming cameras, the calibration is carried out by using a grid pattern of known dimen...

Today's robots are able to perform more and more complex tasks, which usually require a high degree of interaction with the environment they have to operate in. As a consequence, robotic systems should have a deep and specific knowledge of their workspaces, which goes far beyond a simple metric representation a robotic system can build up through S...

Mobility in large touristic cities (such as Rome and Venice), where needs of citizen and tourists are different(and sometimes even conflicting), is a very relevant problem and infomobility is thus increasingly important. Since active technologies, requiring the passengers to wear some devices(e.g., RFID devices) are not commonly available and canno...