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2023
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THE D.8.8.1 - State of the art for digital models of cultured neural networks
Lagani G, Falchi F, Amato G
THE deliverable 8.8.1 is a technical report about current state-of-the-art approaches in the field of bio-inspired technologies for Artificial Intelligence (AI)
Lagani G, Falchi F, Amato G
THE deliverable 8.8.1 is a technical report about current state-of-the-art approaches in the field of bio-inspired technologies for Artificial Intelligence (AI)
2023
Other
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THE D.3.2.1 - AA@THE User needs, technical requirements and specifications
Pratali L, Campana M G, Delmastro F, Di Martino F, Pescosolido L, Barsocchi P, Broccia G, Ciancia V, Gennaro C, Girolami M, Lagani G, La Rosa D, Latella D, Magrini M, Manca M, Massink M, Mattioli A, Moroni D, Palumbo F, Paradisi P, Paternò F, Santoro C, Sebastiani L, Vairo C
Deliverable D3.2.1 del progetto PNRR Ecosistemi ed innovazione - THE
Pratali L, Campana M G, Delmastro F, Di Martino F, Pescosolido L, Barsocchi P, Broccia G, Ciancia V, Gennaro C, Girolami M, Lagani G, La Rosa D, Latella D, Magrini M, Manca M, Massink M, Mattioli A, Moroni D, Palumbo F, Paradisi P, Paternò F, Santoro C, Sebastiani L, Vairo C
Deliverable D3.2.1 del progetto PNRR Ecosistemi ed innovazione - THE
2023
Conference article
Open Access
AIMH Lab for a susteinable bio-inspired AI
Lagani G, Falchi F, Gennaro C, Amato G
In this short paper, we report the activities of the Artificial Intelligence for Media and Humanities (AIMH) laboratory of the ISTI-CNR related to Sustainable AI. In particular, we discuss the problem of the environmental impact of AI research, and we discuss a research direction aimed at creating effective intelligent systems with a reduced ecological footprint. The proposal is based on bio-inspired learning, which takes inspiration from the biological processes underlying human intelligence in order to produce more energy-efficient AI systems. In fact, biological brains are able to perform complex computations, with a power consumption which is orders of magnitude smaller than that of traditional AI. The ability to control and replicate these biological processes reveals promising results towards the realization of sustainable AISource: CEUR WORKSHOP PROCEEDINGS, pp. 575-584. Pisa, Italy, 29-30/05/2023
Lagani G, Falchi F, Gennaro C, Amato G
In this short paper, we report the activities of the Artificial Intelligence for Media and Humanities (AIMH) laboratory of the ISTI-CNR related to Sustainable AI. In particular, we discuss the problem of the environmental impact of AI research, and we discuss a research direction aimed at creating effective intelligent systems with a reduced ecological footprint. The proposal is based on bio-inspired learning, which takes inspiration from the biological processes underlying human intelligence in order to produce more energy-efficient AI systems. In fact, biological brains are able to perform complex computations, with a power consumption which is orders of magnitude smaller than that of traditional AI. The ability to control and replicate these biological processes reveals promising results towards the realization of sustainable AISource: CEUR WORKSHOP PROCEEDINGS, pp. 575-584. Pisa, Italy, 29-30/05/2023
See at:
ceur-ws.org 
| CNR IRIS | ISTI Repository | CNR IRIS 
2023
Other
Open Access
AIMH Research Activities 2023
Aloia N., Amato G., Bartalesi Lenzi V., Bianchi L., Bolettieri P., Bosio C., Carraglia M., Carrara F., Casarosa V., Ciampi L., Coccomini D. A., Concordia C., Corbara S., De Martino C., Di Benedetto M., Esuli A., Falchi F., Fazzari E., Gennaro C., Lagani G., Lenzi E., Meghini C., Messina N., Molinari A., Moreo Fernandez A., Nardi A., Pedrotti A., Pratelli N., Puccetti G., Rabitti F., Savino P., Sebastiani F., Sperduti G., Thanos C., Trupiano L., Vadicamo L., Vairo C., Versienti L.
The AIMH (Artificial Intelligence for Media and Humanities) laboratory is dedicated to exploring and pushing the boundaries in the field of Artificial Intelligence, with a particular focus on its application in digital media and humanities. This lab's objective is to enhance the current state of AI technology particularly on deep learning, text analysis, computer vision, multimedia information retrieval, multimedia content analysis, recognition, and retrieval. This report encapsulates the laboratory's progress and activities throughout the year 2023.DOI: 10.32079/isti-ar-2023/001
Metrics:
Aloia N., Amato G., Bartalesi Lenzi V., Bianchi L., Bolettieri P., Bosio C., Carraglia M., Carrara F., Casarosa V., Ciampi L., Coccomini D. A., Concordia C., Corbara S., De Martino C., Di Benedetto M., Esuli A., Falchi F., Fazzari E., Gennaro C., Lagani G., Lenzi E., Meghini C., Messina N., Molinari A., Moreo Fernandez A., Nardi A., Pedrotti A., Pratelli N., Puccetti G., Rabitti F., Savino P., Sebastiani F., Sperduti G., Thanos C., Trupiano L., Vadicamo L., Vairo C., Versienti L.
The AIMH (Artificial Intelligence for Media and Humanities) laboratory is dedicated to exploring and pushing the boundaries in the field of Artificial Intelligence, with a particular focus on its application in digital media and humanities. This lab's objective is to enhance the current state of AI technology particularly on deep learning, text analysis, computer vision, multimedia information retrieval, multimedia content analysis, recognition, and retrieval. This report encapsulates the laboratory's progress and activities throughout the year 2023.DOI: 10.32079/isti-ar-2023/001
Metrics:
See at:
CNR IRIS | ISTI Repository | CNR IRIS
2023
Other
Open Access
D3.2.1: AA@THE User needs, technical requirements and specifications
Lorenza Pratali, Franca Delmastro, Mattia Campana, Flavio Di Martino, Loreto Pescosolido, Paolo Barsocchi, Giovanna Broccia, Vincenzo Ciancia, Claudio Gennaro, Michele Girolami, Gabriele Lagani, Diego Latella, Massimo Magrini, Marco Manca, Mieke Massink, Andrea Mattioli, Davide Moroni, Filippo Palumbo, Paolo Paradisi, Fabio Paternò, Laura Sebastiani, Claudio Vairo, Carmelina Santoro, Davide La Rosa
The objective of this deliverable is to compile a comprehensive report that describes the user needs, requirements, and technical specifications necessary to successfully implement the pilot study. To achieve this, it is crucial to establish contacts with specific associations and medical experts, which, collaboratively, will help to establish exclusion and inclusion criteria for the target population of healthy adults. Furthermore, another related objective is to define the different categories of users that will interact with the system and their specific needs. This holistic approach will ensure that the system is designed and developed to satisfy the diverse needs of the users and be aligned with the goals of the project. To achieve the milestone M3.2.1, we made significant progresses in the definition of the pilot study for the AA@THE subproject. One of our key achievements is the successful description of users’ needs, requirements, and technical specifications necessary for the study. We worked closely with both a specialized association of personal trainers for Adapted Physical Activity (APA) for older adults, already active in the area of Pisa, and the medical partner who played a crucial role in providing valuable insights and expertise to establish exclusion and inclusion criteria for the target population of healthy adults. In this milestone, we also defined the activities and services that we intend to offer. Specifically, we plan to provide technological systems aimed at monitoring physical and cognitive training processes, as well as stability evaluations, by instrumenting a gym dedicated to active and healthy ageing, which is located within the CNR research area in Pisa. Additionally, we will conduct sleep, nutrition, and sedentary assessments at the volunteers' homes. Furthermore, we successfully defined the different user categories involved in the study. To facilitate the recruitment process and people engagement, on January 17th 2023, we organized an open day in collaboration with the gym association where we presented the overall objectives of the project and we collected feedbacks from a group of healthy adults over 65, already involved in APA training. This allowed us to gain a comprehensive understanding of the users' specific needs in terms of system interactions, thus establishing the system requirements and technical specifications of the AA@THE ecosystem. In parallel, a specific action on “Automatic Support of Medical Image Analysis” has been initiated by members of the “Formal Methods and Tools” group at CNR-ISTI. Such an action aims at leveraging Formal Methods in Computer Science, Logic and Model Checking to augment state-of-the-art machine learning techniques for automatic medical image analysis, enabling end-users to make specific assumptions on the level of accountability and affordability of the system. The methodology is based on a strict intertwining between theory and experimentation, with the development of new theoretical foundations for model reduction and efficient model checking, and experimentation and finalization of a graphical user interface that is being evaluated from the points of view of usability and of cognitive load. Moreover, the design and implementation of a suitable GUI able to support the analysis of medical images has been conducted and tested with small groups of people derived from the hospital in Lucca. The proposed GUI prototype has been evaluated from a cognitive point of view in order to allow easy employment with little training, for general practitioners and caregivers who may lack the technical skills required to use fully-fledged medical imaging programs.Project(s): Tuscany Health Ecosystem
Lorenza Pratali, Franca Delmastro, Mattia Campana, Flavio Di Martino, Loreto Pescosolido, Paolo Barsocchi, Giovanna Broccia, Vincenzo Ciancia, Claudio Gennaro, Michele Girolami, Gabriele Lagani, Diego Latella, Massimo Magrini, Marco Manca, Mieke Massink, Andrea Mattioli, Davide Moroni, Filippo Palumbo, Paolo Paradisi, Fabio Paternò, Laura Sebastiani, Claudio Vairo, Carmelina Santoro, Davide La Rosa
The objective of this deliverable is to compile a comprehensive report that describes the user needs, requirements, and technical specifications necessary to successfully implement the pilot study. To achieve this, it is crucial to establish contacts with specific associations and medical experts, which, collaboratively, will help to establish exclusion and inclusion criteria for the target population of healthy adults. Furthermore, another related objective is to define the different categories of users that will interact with the system and their specific needs. This holistic approach will ensure that the system is designed and developed to satisfy the diverse needs of the users and be aligned with the goals of the project. To achieve the milestone M3.2.1, we made significant progresses in the definition of the pilot study for the AA@THE subproject. One of our key achievements is the successful description of users’ needs, requirements, and technical specifications necessary for the study. We worked closely with both a specialized association of personal trainers for Adapted Physical Activity (APA) for older adults, already active in the area of Pisa, and the medical partner who played a crucial role in providing valuable insights and expertise to establish exclusion and inclusion criteria for the target population of healthy adults. In this milestone, we also defined the activities and services that we intend to offer. Specifically, we plan to provide technological systems aimed at monitoring physical and cognitive training processes, as well as stability evaluations, by instrumenting a gym dedicated to active and healthy ageing, which is located within the CNR research area in Pisa. Additionally, we will conduct sleep, nutrition, and sedentary assessments at the volunteers' homes. Furthermore, we successfully defined the different user categories involved in the study. To facilitate the recruitment process and people engagement, on January 17th 2023, we organized an open day in collaboration with the gym association where we presented the overall objectives of the project and we collected feedbacks from a group of healthy adults over 65, already involved in APA training. This allowed us to gain a comprehensive understanding of the users' specific needs in terms of system interactions, thus establishing the system requirements and technical specifications of the AA@THE ecosystem. In parallel, a specific action on “Automatic Support of Medical Image Analysis” has been initiated by members of the “Formal Methods and Tools” group at CNR-ISTI. Such an action aims at leveraging Formal Methods in Computer Science, Logic and Model Checking to augment state-of-the-art machine learning techniques for automatic medical image analysis, enabling end-users to make specific assumptions on the level of accountability and affordability of the system. The methodology is based on a strict intertwining between theory and experimentation, with the development of new theoretical foundations for model reduction and efficient model checking, and experimentation and finalization of a graphical user interface that is being evaluated from the points of view of usability and of cognitive load. Moreover, the design and implementation of a suitable GUI able to support the analysis of medical images has been conducted and tested with small groups of people derived from the hospital in Lucca. The proposed GUI prototype has been evaluated from a cognitive point of view in order to allow easy employment with little training, for general practitioners and caregivers who may lack the technical skills required to use fully-fledged medical imaging programs.Project(s): Tuscany Health Ecosystem