most citedShape and Style GAN-based Multispectral Data Augmentation for Crop/Weed Segmentation in Precision Farming

25 citations · 27 across the 7 of their papers we have counts for

collaborators

7 papers

cs.CV2024

Real-Time Multimodal Signal Processing for HRI in RoboCup: Understanding a Human Referee

Filippo Ansalone, Flavio Maiorana, Daniele Affinita +8

Advancing human-robot communication is crucial for autonomous systems operating in dynamic environments, where accurate real-time interpretation of human signals is essential. Robo…

cs.CV202425 cited

Shape and Style GAN-based Multispectral Data Augmentation for Crop/Weed Segmentation in Precision Farming

Mulham Fawakherji, Vincenzo Suriani, Daniele Nardi +1

The use of deep learning methods for precision farming is gaining increasing interest. However, collecting training data in this application field is particularly challenging and c…

cs.RO2024

LLCoach: Generating Robot Soccer Plans using Multi-Role Large Language Models

Michele Brienza, Emanuele Musumeci, Vincenzo Suriani +4

The deployment of robots into human scenarios necessitates advanced planning strategies, particularly when we ask robots to operate in dynamic, unstructured environments. RoboCup o…

cs.CL20242 cited

LLM Based Multi-Agent Generation of Semi-structured Documents from Semantic Templates in the Public Administration Domain

Emanuele Musumeci, Michele Brienza, Vincenzo Suriani +2

In the last years' digitalization process, the creation and management of documents in various domains, particularly in Public Administration (PA), have become increasingly complex…

cs.RO2024

Multi-Agent Coordination for a Partially Observable and Dynamic Robot Soccer Environment with Limited Communication

Daniele Affinita, Flavio Volpi, Valerio Spagnoli +3

RoboCup represents an International testbed for advancing research in AI and robotics, focusing on a definite goal: developing a robot team that can win against the human world soc…

cs.RO2023

Enhancing Graph Representation of the Environment through Local and Cloud Computation

Francesco Argenziano, Vincenzo Suriani, Daniele Nardi

Enriching the robot representation of the operational environment is a challenging task that aims at bridging the gap between low-level sensor readings and high-level semantic unde…