4 Contributo in Atti di Convegno (Proceeding)

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4.1 Contributo in Atti di convegno 11972
4.2 Abstract in Atti di convegno 2268
4.3 Poster 285

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Pompeii Robotic Vision: Unveiling Flaws Through Advanced Inspection

Archaeological site inspection is crucial for detecting damages and alterations to ancient buildings, structures, and monuments, regardless of their magnitude. This proactive approach helps to limit their degradation due to anthropic and environmental factors, currently exacerbated by massive tourism and climate change. As a result, their conservation and longevity can be ensured. Regular and systematic monitoring is a recognized strategy for effectively preventing structural damage, however,...

A Novel Two-Step Approach for Recreational Fishers Detection and Classification

The detection of illegal and unregulated fishing activities remains a significant challenge for environmentally sustainable fishing and regulatory enforcement. Manual surveying and electronic monitoring systems require extensive human efforts and intervention adding to inefficiencies and scalability issues. Advances in deep learning based image analysis provide an alternative for implementing automated monitoring strategies to realize the sustainability goals for fisheries. This study introdu...

A Lightweight Deep Learning Approach for Lithium-ion Battery RUL Estimation

Lithium-ion batteries represent a pivotal component within contemporary energy storage solutions, exhibiting a diverse range of applications spanning from consumer electronics to electric vehicles and renewable energy systems. Nevertheless, the progressive degradation of these batteries, resulting in a reduction in capacity and performance, poses significant challenges in terms of system safety and reliability. In this context, the evaluation of the Remaining Useful Life (RUL) plays a central...

Distributed Learning Technique with Deep ESN-Based Models for Energy Forecasting

Advances in machine learning (ML) have opened up new opportunities to include decision-making capabilities in Internet of Things (IoT) nodes. This opportunity is complex to address, since conventional ML implementations are computationally intensive, thus reducing the possibility of implementing them on resource-constrained systems. In addition, when nodes in a network grow significantly, centralized data processing creates new challenges such as latency, resource efficiency, privacy, bandwid...

Integrating LLMs into Collaborative Robotics for Automated Zipped Apparel Disassembly

In order to successfully integrate circular economy principles into current value chains, it is crucial to ensure the economic sustainability of disassembly processes. Recent scientific and technological innovations, including Large Language Models (LLMs) in artificial intelligence (AI), are greatly accelerating progress in enhancing robotic capabilities. Dismantling is the first step in the re-manufacturing, repair, and recycling processes of end-of-life (EoL) products. Traditionally, this o...

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