Robotics, Vision and Intelligent Technologies. Artificial Intelligence, Machine Learning & Computer Vision
University of Alicante, Spain
Joined March 2019
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Proud of this great teamwork between the Rovit group and retinalmicroscopy.com/!
#ParkinsonsDisease #Neuroscience #Biomarkers #OpticNerve #Research #Rovit
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The work explores two key areas in next-generation robotics: real-time Digital Shadows for physical-to-virtual synchronization using ROS 2, computer vision and NVIDIA Isaac Sim , and VLN-Pilot, a framework that uses Vision-Language Models to autonomously navigate indoor
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drones from natural-language instructions.
Two exciting steps forward at the intersection of robotics, AI, computer vision and simulation.
#WAF2026 #Robotics #ArtificialIntelligence #ComputerVision #DigitalTwin #VisionLanguageModels #AutonomousRobots
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We evaluated PICoS in a pilot study with children with different cognitive profiles, using two Go/No-Go-style activities focused on attention, turn-taking and response withholding.
The study was designed to assess technical feasibility and acceptability.
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The results are encouraging:4/5 participants selected the highest enjoyment rating, and all 5 said they would like to use the system again.
There is still much to explore,especially with larger and longitudinal studies.
#VirtualReality #ArtificialIntelligence #GaussianSplatting
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We are delighted to announce that TEACH-AI has been funded by the Generalitat Valenciana through the Prometeo Programme for Research Groups of Excellence. The project will explore how AI can support more inclusive, evidence-based education. 🧵
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At its core, the project will use multi-agent simulations and skill graphs to model teachers, students, competencies and learning pathways—including diverse and neurodivergent profiles such as ASD and ADHD.
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Led by Rosabel Roig-Vila and Miguel Cazorla at the University of Alicante, TEACH-AI will deliver open-source tools, FAIR datasets and a validated prototype for teacher training, educational planning and inclusive decision-making.
#AI #EdTech #Education
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Our experiments show that many current detection models experience a significant performance drop on FFA, especially when analyzed across demographic subgroups. This highlights the need for benchmarks that evaluate not only accuracy, but also generalization and fairness.
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We hope this resource contributes to the development of more reliable, transparent, and responsible deepfake detection systems.
#Deepfakes #ComputerVision #AI #FairAI #SyntheticMedia #DeepfakeDetection #MachineLearning
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