5 accepted papers
In spite of the great potential of large language models (LLMs) across various tasks, their deployment on resource-constrained devices remains challenging due to their excessive computational and memory demands. Quantization has emerged as an effective solution by storing weights in reduced precisio…
"Semantic segmentation arises as the backbone of many vision systems, spanning from self-driving cars and robot navigation to augmented reality and teleconferencing. Frequently operating under stringent latency constraints within a limited resource envelope, optimising for efficient execution become…
Deep Learning-based object detectors enhance the capabilities of remote sensing platforms, such as Unmanned Aerial Vehicles (UAVs), in a wide spectrum of machine vision applications. However, the integration of deep learning introduces heavy computational requirements, preventing the deployment of s…
This letter addresses the problem of distinguishing unexpected collisions from voluntary contacts during human-robot collaboration. The objective of this letter is to improve the safety of the operator during the interaction with the robot. Based on the observation that cooperation forces present di
Nowadays, Unmanned Aerial Vehicles (UAVs)are becoming increasingly popular facilitated by their extensive availability. Autonomous navigation methods can act as an enabler for the safe deployment of drones on a wide range of real-world civilian applications. In this work, we introduce a self-supervi…