AI-ISA Research Group · ICAR-CNR

Artificial Intelligence
in Image & Signal
Analysis

We investigate AI models and methods for the automated analysis of images, signals, and complex data. Our research integrates computer vision, pattern recognition, signal processing, and deep learning to advance scientific understanding and develop novel solutions in several fields, including healthcare, agrifood, and environment.

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About us

A Research Group of ICAR-CNR

The AI-ISA group has extensive experience in Computer Vision, Pattern Recognition, and Signal Analysis, as well as deep expertise in Deep and Machine Learning. We are part of ICAR – the Institute for High Performance Computing and Networking - of the Italian National Research Council (CNR).

Our work focuses on designing AI models for the automatic analysis of images, signals, and data — with particular interest in Medical/Biological Imaging, Healthcare, and Agrifood & Environment.

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CNR

ICAR

DIITET

Our research

Research Topics

Core areas where our group develops methods, tools, and applications.

Computer Vision

Design of new learning networks and algorithms for feature extraction, pattern identification, and classification in images — from object detection to semantic segmentation and scene understanding.

Signal Processing

Analysis of biosignals, audio, and complex multivariate signals using advanced AI techniques. We extract meaningful patterns from temporal data for healthcare monitoring and environmental sensing.

Machine Learning

Development of end-to-end Deep/Machine Learning models, including generative models for synthesising patterns with characteristics similar to real-world data, covering supervised, unsupervised, and self-supervised paradigms.

Healthcare AI

Application of AI to Medical/Biological Imaging and patient monitoring. We develop intelligent diagnostic tools that assist clinicians through automated image interpretation and signal-based health assessment.

Explainability & XAI

Development of models for the interpretability and explainability of machine learning systems, enabling users to understand and trust the predictions produced by complex AI models.

Edge AI & Federated Learning

Design of AI models for mobile and resource-constrained devices with low-latency inference, alongside innovative Federated Learning algorithms based on Computational Intelligence and Soft Computing for Neuroevolution.

Research

Our Projects

Funded research projects at European, national, and regional level.

European 2025–2029

EXPLORER

Portable photonic technologies for in-situ study of extreme natural environments, integrating AI and Deep Learning for image analysis. Funded by Horizon MSCA-2024.

European 2023–2026

DS4Health

EU Digital Europe project designing an international Master's in Digital Health, training professionals in advanced digital skills for a modern, citizen-centred healthcare system.

National 2022–2026

D3_4Health

PNRR/PNC NextGenerationEU project on digital and biological twins via AI and data mining for management of cancer, diabetes and multiple sclerosis. ICAR coord.: Giovanna Sannino.

National 2023–2025

TRaaS

PRIN 2022 project on Tele-Rehabilitation as a Service — Cloud/Edge framework for de-hospitalised rehabilitation of patients with severe acquired brain injury. ICAR coord.: Giovanna Sannino.

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Ready to take the first step?

We welcome talented researchers, PhD students, and collaborators who share our passion for AI and signal analysis.

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Artificial Intelligence in Image & Signal Analysis