Robotics, Vision and Intelligent Technologies
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Universidad de Alicante

Escuela Politécnica Superior III
Ctra. San Vicente, S/N
E-03690 San Vicente del Raspeig (Alicante)
SPAIN

german.gonzalez@ua.es

Active projects

2025-2026

Detección de eventos en pádel​

This private project focused on detecting events in a padel court.
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2025-2026

Consultoría para el análisis del punto de partida, definición de casos de uso y redacción del documento de especificaciones técnicas del Gemelo Digital Rodes

The Rodes Digital Twin project is designed as a tool for monitoring and simulating scenarios in the technology park, enabling data-driven management, energy efficiency, and improved user comfort and safety. The project constitutes the technical and administrative proposal for the consulting services contract aimed at analyzing the starting point, defining use cases, and drafting the technical specifications document for the Rodes Digital Twin.
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2025-2026

Uso de la inteligencia Artificial como Herramienta Clínica para Predecir la Aparición de Retinopatía Diabética Mediante el Uso de Imágenes de Tomografía de Coherencia Óptica (OCT) y Angiografía por Tomografía de Coherencia Óptica (OCTA).

La diabetes mellitus es una enfermedad metabólica crónica que ha aumentado notablemente su prevalencia en España, generando importantes complicaciones como la retinopatía diabética (RD), principal causa de ceguera en edad laboral. El diagnóstico precoz de la RD es esencial, ya que...
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2025-2026

CYPE: Smart construction manager

This project aims to digitize the construction process from its earliest stages to its final stages. We have developed 3D reconstruction techniques for VR that allow the progress of the work to be verified.
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2025-2028

Spectroscopic Analysis and Recognition Techniques with Optimization through Artificial Intelligence

The project proposes an in-depth exploration of advanced machine learning techniques for the automated classification of stellar spectra, aiming to significantly reduce computation time compared to current methods used by Astro+. Beyond improving efficiency, the project envisions the development of models capable of directly determining stellar parameters through deep learning, eliminating the need for manual model fitting. This approach would represent a major step toward fully automated and more efficient spectroscopic analysis.
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