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20172026
most citedShape and Style GAN-based Multispectral Data Augmentation for Crop/Weed Segmentation in Precision Farming

25 citations · 43 across the 30 of their papers we have counts for

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cs.CV2026

An LLM-Based Automatic Sportscast Solution for Robot Soccer Matches

Francesco Petri, Michele Brienza, Daniele Nardi +3

RoboCup has always been a scenario to develop systems that solve real-world problems. Driven by the main goal of playing against the 2050 FIFA World Cup champions, the RoboCup Socc…

cs.CV2025

Self-supervised Feature Extraction for Enhanced Ball Detection on Soccer Robots

Can Lin, Daniele Affinita, Marco E. P. Zimmatore +3

Robust and accurate ball detection is a critical component for autonomous humanoid soccer robots, particularly in dynamic and challenging environments such as RoboCup outdoor field…

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.CV2024★ 25 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.CV2017★ 2 cited

Machine Learning for RealisticBall Detection in RoboCup SPL

Domenico Bloisi, Francesco Del Duchetto, Tiziano Manoni +1

In this technical report, we describe the use of a machine learning approach for detecting the realistic black and white ball currently in use in the RoboCup Standard Platform Leag…