12 results on '"Gennaro, Claudio"'
Search Results
2. The Face Deepfake Detection Challenge.
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Guarnera, Luca, Giudice, Oliver, Guarnera, Francesco, Ortis, Alessandro, Puglisi, Giovanni, Paratore, Antonino, Bui, Linh M. Q., Fontani, Marco, Coccomini, Davide Alessandro, Caldelli, Roberto, Falchi, Fabrizio, Gennaro, Claudio, Messina, Nicola, Amato, Giuseppe, Perelli, Gianpaolo, Concas, Sara, Cuccu, Carlo, Orrù, Giulia, Marcialis, Gian Luca, and Battiato, Sebastiano
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MACHINE learning ,DEEP learning ,ARTIFICIAL intelligence ,DEEPFAKES ,DISCRETE cosine transforms - Abstract
Multimedia data manipulation and forgery has never been easier than today, thanks to the power of Artificial Intelligence (AI). AI-generated fake content, commonly called Deepfakes, have been raising new issues and concerns, but also new challenges for the research community. The Deepfake detection task has become widely addressed, but unfortunately, approaches in the literature suffer from generalization issues. In this paper, the Face Deepfake Detection and Reconstruction Challenge is described. Two different tasks were proposed to the participants: (i) creating a Deepfake detector capable of working in an "in the wild" scenario; (ii) creating a method capable of reconstructing original images from Deepfakes. Real images from CelebA and FFHQ and Deepfake images created by StarGAN, StarGAN-v2, StyleGAN, StyleGAN2, AttGAN and GDWCT were collected for the competition. The winning teams were chosen with respect to the highest classification accuracy value (Task I) and "minimum average distance to Manhattan" (Task II). Deep Learning algorithms, particularly those based on the EfficientNet architecture, achieved the best results in Task I. No winners were proclaimed for Task II. A detailed discussion of teams' proposed methods with corresponding ranking is presented in this paper. [ABSTRACT FROM AUTHOR]
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- 2022
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3. Boosting a Low-Cost Smart Home Environment with Usage and Access Control Rules.
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Barsocchi, Paolo, Calabrò, Antonello, Ferro, Erina, Gennaro, Claudio, Marchetti, Eda, and Vairo, Claudio
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HOME automation ,HOME environment ,ACCESS control ,MACHINE learning ,UBIQUITOUS computing - Abstract
Smart Home has gained widespread attention due to its flexible integration into everyday life. Pervasive sensing technologies are used to recognize and track the activities that people perform during the day, and to allow communication and cooperation of physical objects. Usually, the available infrastructures and applications leveraging these smart environments have a critical impact on the overall cost of the Smart Home construction, require to be preferably installed during the home construction and are still not user-centric. In this paper, we propose a low cost, easy to install, user-friendly, dynamic and flexible infrastructure able to perform runtime resources management by decoupling the different levels of control rules. The basic idea relies on the usage of off-the-shelf sensors and technologies to guarantee the regular exchange of critical information, without the necessity from the user to develop accurate models for managing resources or regulating their access/usage. This allows us to simplify the continuous updating and improvement, to reduce the maintenance effort and to improve residents’ living and security. A first validation of the proposed infrastructure on a case study is also presented. [ABSTRACT FROM AUTHOR]
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- 2018
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4. Deep learning for decentralized parking lot occupancy detection.
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Amato, Giuseppe, Carrara, Fabio, Falchi, Fabrizio, Gennaro, Claudio, Meghini, Carlo, and Vairo, Claudio
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DEEP learning , *DECENTRALIZATION in management , *PARKING lots , *INFORMATION theory , *ARTIFICIAL neural networks - Abstract
A smart camera is a vision system capable of extracting application-specific information from the captured images. The paper proposes a decentralized and efficient solution for visual parking lot occupancy detection based on a deep Convolutional Neural Network (CNN) specifically designed for smart cameras. This solution is compared with state-of-the-art approaches using two visual datasets: PKLot, already existing in literature, and CNRPark-EXT. The former is an existing dataset, that allowed us to exhaustively compare with previous works. The latter dataset has been created in the context of this research, accumulating data across various seasons of the year, to test our approach in particularly challenging situations, exhibiting occlusions, and diverse and difficult viewpoints. This dataset is public available to the scientific community and is another contribution of our research. Our experiments show that our solution outperforms and generalizes the best performing approaches on both datasets. The performance of our proposed CNN architecture on the parking lot occupancy detection task, is comparable to the well-known AlexNet, which is three orders of magnitude larger. [ABSTRACT FROM AUTHOR]
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- 2017
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5. A cognitive robotic ecology approach to self-configuring and evolving AAL systems.
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Dragone, Mauro, Amato, Giuseppe, Bacciu, Davide, Chessa, Stefano, Coleman, Sonya, Rocco, Maurizio Di, Gallicchio, Claudio, Gennaro, Claudio, Lozano, Hector, Maguire, Liam, McGinnity, Martin, Micheli, Alessio, O׳Hare, Gregory M.P., Renteria, Arantxa, Saffiotti, Alessandro, Vairo, Claudio, and Vance, Philip
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COGNITION , *ROBOTICS , *MOBILE robots , *WIRELESS sensor networks , *EMBEDDED computer systems , *COMPUTER algorithms , *INFORMATION processing - Abstract
Robotic ecologies are systems made out of several robotic devices, including mobile robots, wireless sensors and effectors embedded in everyday environments, where they cooperate to achieve complex tasks. This paper demonstrates how endowing robotic ecologies with information processing algorithms such as perception, learning, planning, and novelty detection can make these systems able to deliver modular, flexible, manageable and dependable Ambient Assisted Living (AAL) solutions. Specifically, we show how the integrated and self-organising cognitive solutions implemented within the EU project RUBICON (Robotic UBIquitous Cognitive Network) can reduce the need of costly pre-programming and maintenance of robotic ecologies. We illustrate how these solutions can be harnessed to (i) deliver a range of assistive services by coordinating the sensing & acting capabilities of heterogeneous devices, (ii) adapt and tune the overall behaviour of the ecology to the preferences and behaviour of its inhabitants, and also (iii) deal with novel events, due to the occurrence of new user׳s activities and changing user׳s habits. [ABSTRACT FROM AUTHOR]
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- 2015
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6. An embedded toolset for human activity monitoring in critical environments.
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Di Benedetto, Marco, Carrara, Fabio, Ciampi, Luca, Falchi, Fabrizio, Gennaro, Claudio, and Amato, Giuseppe
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HUMAN activity recognition , *SAFETY appliances , *PERSONAL protective equipment , *COVID-19 , *SOCIAL distancing - Abstract
In many working and recreational activities, there are scenarios where both individual and collective safety have to be constantly checked and properly signaled, as occurring in dangerous workplaces or during pandemic events like the recent COVID-19 disease. From wearing personal protective equipment to filling physical spaces with an adequate number of people, it is clear that a possibly automatic solution would help to check compliance with the established rules. Based on an off-the-shelf compact and low-cost hardware, we present a deployed real use-case embedded system capable of perceiving people's behavior and aggregations and supervising the appliance of a set of rules relying on a configurable plug-in framework. Working on indoor and outdoor environments, we show that our implementation of counting people aggregations, measuring their reciprocal physical distances, and checking the proper usage of protective equipment is an effective yet open framework for monitoring human activities in critical conditions. • Monitoring compliance with safety rules is crucial in critical environments. • Presenting a Computer Vision-based AI-assisted system to monitor human activities. • Modular architecture for pedestrian detection, counting, distancing, and PPE detection. • Two novel datasets of PPE detection and overall system evaluation in a real scenario. • State-of-the-art trained models in a deployed real use-case scenario in Pisa, Italy. [ABSTRACT FROM AUTHOR]
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- 2022
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7. MultiMedia Modeling : 30th International Conference, MMM 2024, Amsterdam, The Netherlands, January 29 – February 2, 2024, Proceedings, Part IV
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Stevan Rudinac, Alan Hanjalic, Cynthia Liem, Marcel Worring, Björn Þór Jónsson, Bei Liu, Yoko Yamakata, Stevan Rudinac, Alan Hanjalic, Cynthia Liem, Marcel Worring, Björn Þór Jónsson, Bei Liu, and Yoko Yamakata
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- Computer vision, Image processing, Pattern recognition systems, Application software, Information storage and retrieval systems, Machine learning
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This book constitutes the refereed proceedings of the 30th International Conference on MultiMedia Modeling, MMM 2024, held in Amsterdam, The Netherlands, during January 29–February 2, 2024.The 112 full papers included in this volume were carefully reviewed and selected from 297 submissions. The MMM conference were organized in topics related to multimedia modelling, particularly: audio, image, video processing, coding and compression; multimodal analysis for retrieval applications, and multimedia fusion methods.
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- 2024
8. MultiMedia Modeling : 29th International Conference, MMM 2023, Bergen, Norway, January 9–12, 2023, Proceedings, Part I
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Duc-Tien Dang-Nguyen, Cathal Gurrin, Martha Larson, Alan F. Smeaton, Stevan Rudinac, Minh-Son Dao, Christoph Trattner, Phoebe Chen, Duc-Tien Dang-Nguyen, Cathal Gurrin, Martha Larson, Alan F. Smeaton, Stevan Rudinac, Minh-Son Dao, Christoph Trattner, and Phoebe Chen
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- Computer vision, Machine learning, Pattern recognition systems, Social sciences—Data processing
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The two-volume set LNCS 13833 and LNCS 13834 constitutes the proceedings of the 29th International Conference on MultiMedia Modeling, MMM 2023, which took place in Bergen, Norway, during January 9-12, 2023. The 86 papers presented in these proceedings were carefully reviewed and selected from a total of 267 submissions. They focus on topics related to multimedia content analysis; multimedia signal processing and communications; and multimedia applications and services.
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- 2023
9. Image Analysis and Processing – ICIAP 2023 : 22nd International Conference, ICIAP 2023, Udine, Italy, September 11–15, 2023, Proceedings, Part I
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Gian Luca Foresti, Andrea Fusiello, Edwin Hancock, Gian Luca Foresti, Andrea Fusiello, and Edwin Hancock
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- Computer engineering, Computer networks, Machine learning, Education—Data processing, Pattern recognition systems
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This two-volume set LNCS 14233-14234 constitutes the refereed proceedings of the 22nd International Conference on Image Analysis and Processing, ICIAP 2023, held in Udine, Italy, during September 11–15, 2023.The 85 full papers presented together with 7 short papers were carefully reviewed and selected from 144 submissions. The conference focuses on video analysis and understanding; pattern recognition and machine learning; deep learning; multi-view geometry and 3D computer vision; image analysis, detection and recognition; multimedia; biomedical and assistive technology; digital forensics and biometrics; image processing for cultural heritage; and robot vision.
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- 2023
10. Image Analysis and Processing – ICIAP 2022 : 21st International Conference, Lecce, Italy, May 23–27, 2022, Proceedings, Part III
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Stan Sclaroff, Cosimo Distante, Marco Leo, Giovanni M. Farinella, Federico Tombari, Stan Sclaroff, Cosimo Distante, Marco Leo, Giovanni M. Farinella, and Federico Tombari
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- Computer vision, Computer engineering, Computer networks, Machine learning, Education—Data processing, Pattern recognition systems
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The proceedings set LNCS 13231, 13232, and 13233 constitutes the refereed proceedings of the 21st International Conference on Image Analysis and Processing, ICIAP 2022, which was held during May 23-27, 2022, in Lecce, Italy,The 168 papers included in the proceedings were carefully reviewed and selected from 307 submissions. They deal with video analysis and understanding; pattern recognition and machine learning; deep learning; multi-view geometry and 3D computer vision; image analysis, detection and recognition; multimedia; biomedical and assistive technology; digital forensics and biometrics; image processing for cultural heritage; robot vision; etc.
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- 2022
11. MultiMedia Modeling : 27th International Conference, MMM 2021, Prague, Czech Republic, June 22–24, 2021, Proceedings, Part II
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Jakub Lokoč, Tomáš Skopal, Klaus Schoeffmann, Vasileios Mezaris, Xirong Li, Stefanos Vrochidis, Ioannis Patras, Jakub Lokoč, Tomáš Skopal, Klaus Schoeffmann, Vasileios Mezaris, Xirong Li, Stefanos Vrochidis, and Ioannis Patras
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- Database management, Machine learning, Artificial intelligence, Image processing—Digital techniques, Computer vision, Application software, Computers, Special purpose
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The two-volume set LNCS 12572 and 1273 constitutes the thoroughly refereed proceedings of the 27th International Conference on MultiMedia Modeling, MMM 2021, held in Prague, Czech Republic, in June2021. Of the 211 submitted regular papers, 40 papers were selected for oral presentation and 33 for poster presentation; 16 special session papers were accepted as well as 2 papers for a demo presentation and 17 papers for participation at the Video Browser Showdown 2021. The papers cover topics such as: multimedia indexing; multimedia mining; multimedia abstraction and summarization; multimedia annotation, tagging and recommendation; multimodal analysis for retrieval applications; semantic analysis of multimedia and contextual data; multimedia fusion methods; multimedia hyperlinking; media content browsing and retrieval tools; media representation and algorithms; audio, image, video processing, coding and compression; multimedia sensors and interaction modes; multimedia privacy, security and content protection; multimedia standards and related issues; advances in multimedia networking and streaming; multimedia databases, content delivery and transport; wireless and mobile multimedia networking; multi-camera and multi-view systems; augmented and virtual reality, virtual environments; real-time and interactive multimedia applications; mobile multimedia applications; multimedia web applications; multimedia authoring and personalization; interactive multimedia and interfaces; sensor networks; social and educational multimedia applications; and emerging trends.
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- 2021
12. Similarity Search and Applications : 14th International Conference, SISAP 2021, Dortmund, Germany, September 29 – October 1, 2021, Proceedings
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Nora Reyes, Richard Connor, Nils Kriege, Daniyal Kazempour, Ilaria Bartolini, Erich Schubert, Jian-Jia Chen, Nora Reyes, Richard Connor, Nils Kriege, Daniyal Kazempour, Ilaria Bartolini, Erich Schubert, and Jian-Jia Chen
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- Information storage and retrieval systems, Database management, Data mining, Machine learning, Application software
- Abstract
This book constitutes the refereed proceedings of the 14th International Conference on Similarity Search and Applications, SISAP 2021, held in Dortmund, Germany, in September/October 2021. The conference was held virtually due to the COVID-19 pandemic.The 23 full papers presented together with 5 short and 3 doctoral symposium papers were carefully reviewed and selected from 50 submissions. The papers are organized in the topical sections named: Similarity Search and Retrieval; Intrinsic Dimensionality; Clustering and Classification; Applications of Similarity Search; Similarity Search in Graph-Structured Data; Doctoral Symposium.
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- 2021
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