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researcher

G. D’Amico

4 papers hereh-index 4146 citations10 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • middle author4

Across the 4 of 4 papers where every author was matched, so the position is known.

fields
  • cs.CV3
  • cs.RO1
same name
  • G. D’Amico — 4 papers, h 33
  • G. D’Amico — 2 papers, h 21
  • G. D’Amico — 1 paper, h 1
  • G. D’Amico — 1 paper, h 1
  • G. D’Amico — 1 paper, h 0
  • G. d’aMico — 1 paper, h 1

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

collaborators

4 papers

cs.CV2026

Integrating Object Detection, LiDAR-Enhanced Depth Estimation, and Segmentation Models for Railway Environments

Enrico Francesco Giannico, Federico Nesti, Gianluca D'Amico +5

Obstacle detection in railway environments is crucial for ensuring safety. However, very few studies address the problem using a complete, modular, and flexible system that can bot…

cs.CV2026

OSDaR-AR: Enhancing Railway Perception Datasets via Multi-modal Augmented Reality

Federico Nesti, Gianluca D'Amico, Mauro Marinoni +1

Although deep learning has significantly advanced the perception capabilities of intelligent transportation systems, railway applications continue to suffer from a scarcity of high…

cs.CV2025

Towards Railway Domain Adaptation for LiDAR-based 3D Detection: Road-to-Rail and Sim-to-Real via SynDRA-BBox

Xavier Diaz, Gianluca D'Amico, Raul Dominguez-Sanchez +3

In recent years, interest in automatic train operations has significantly increased. To enable advanced functionalities, robust vision-based algorithms are essential for perceiving…

cs.RO2025

SimPRIVE: a Simulation framework for Physical Robot Interaction with Virtual Environments

Federico Nesti, Gianluca D'Amico, Mauro Marinoni +1

The use of machine learning in cyber-physical systems has attracted the interest of both industry and academia. However, no general solution has yet been found against the unpredic…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.