Publications

  1. Garcia-D’Urso, Nahuel, Jorge Azorin-Lopez, and Andres Fuster-Guillo. "Obtención de medidas antropométricas a partir de modelos 3D de cuerpos humanos." Jornadas de Computación Empotrada y Reconfigurable: Computación reconfigurable y SoC (2022).
  2. Garcıa-d’Urso, Nahuel Emiliano, Marcelo Saval-Calvo, Jorge Azorin-Lopez, and Andres Fuster-Guillo. "Automatic Fish Size Estimation from Uncalibrated Fish Market Images Using Computer Vision and Deep Learning." 17th International Conference on Soft Computing Models in Industrial and Environmental Applications (SOCO 2022): Salamanca, Spain, September 5–7, 2022, Proceedings (2022).
  3. Garcia-d’Urso, Nahuel, Alejandro Galan-Cuenca, Paula Pérez-Sánchez, Pau Climent-Pérez, Andres Fuster-Guillo, Jorge Azorin-Lopez, Marcelo Saval-Calvo, Juan Eduardo Guillén-Nieto, and Gabriel Soler-Capdepón. "The DeepFish computer vision dataset for fish instance segmentation, classification, and size estimation." Scientific Data (2022).
  4. Garcia-D'Urso, Nahuel E, Alejandro Galan-Cuenca, Pau Climent-Pérez, Marcelo Saval-Calvo, Jorge Azorin-Lopez, and Andres Fuster-Guillo. "Efficient instance segmentation using deep learning for species identification in fish markets." 2022 International Joint Conference on Neural Networks (IJCNN) (2022).
  5. Climent-Pérez, Pau, Alejandro Galán-Cuenca, Nahuel Emiliano García-d’Urso, Marcelo Saval-Calvo, Jorge Azorin-Lopez, and Andres Fuster-Guillo. "Automatic Fish Size Estimation from Uncalibrated Fish Market Images Using Computer Vision and Deep Learning." 17th International Conference on Soft Computing Models in Industrial and Environmental Applications (SOCO 2022) Salamanca, Spain, September 5–7, 2022, Proceedings (2022).
  6. García-D’urso, Nahuel, Pau Climent-Pérez, Miriam Sánchez-Sansegundo, Ana Zaragoza-Martí, Andrés Fuster-Guilló, and Jorge Azorín-López. "A non-invasive approach for total cholesterol level prediction using machine learning." IEEE Access (2022).
  7. Garcia-D’Urso, Nahuel E, Jorge Azorin-Lopez, and Andres Fuster-Guillo. "A Template-Based Method for Automatic Anthropometric Measurements from Multiple 3D Scans." Proceedings of the International Conference on Ubiquitous Computing & Ambient Intelligence (UCAmI 2022) (2022).
  8. Garcia-D’Urso, Nahuel, Alejandro Galan-Cuenca, Cayetano Manchon-Pernis, Andres Fuster-Guillo, and Jorge Azorin-Lopez. "Arquitectura de visión 3D para medición y visualización del cuerpo humano." Avances en arquitectura y tecnología de computadores, Jornadas SARTECO 20/21 (2021).
  9. Garcia-d’Urso, Nahuel. "Análisis de la evolución morfológica del cuerpo y los datos clínicos de pacientes en tratamiento dietético nutricional." (2021).
  10. Azorin-Lopez, Jorge, Andrés Fuster-Guilló, Marcelo Saval-Calvo, Juan Miguel Castillo Zaragoza, Nahuel Garcia-d’Urso, Luis Fernando Pérez Pérez, Ana Zaragoza Martí, José Antonio Hurtado-Sánchez, Miriam Sanchez-SanSegundo, and Nicolás Ruiz-Robledillo. "Tech4DModelviewerRV." (2021).
  11. Rumbo-Rodríguez, Lorena, Miriam Sánchez-SanSegundo, Rosario Ferrer-Cascales, Nahuel García-D’Urso, Jose A Hurtado-Sánchez, and Ana Zaragoza-Martí. "Comparison of body scanner and manual anthropometric measurements of body shape: a systematic review." International journal of environmental research and public health (2021).
  12. Azorin-Lopez, Jorge, Andrés Fuster-Guilló, Marcelo Saval-Calvo, Víctor Villena Martínez, Juan Miguel Castillo Zaragoza, Nahuel Garcia-d’Urso, Cayetano Manchón Martínez, Rosario Ferrer-Cascales, Ana Zaragoza Martí, and Marc Sebban. "Tech4DScanserver." (2021).
  13. Azorin-Lopez, Jorge, Andrés Fuster-Guilló, Marcelo Saval-Calvo, Victor Villena Martínez, Juan Miguel Castillo Zaragoza, Nahuel Emiliano García D’Urso, Cayetano Manchón Martínez, Rosario Ferrer-Cascales, Luis Fernando Pérez Pérez, and Ana Zaragoza Martí. "Tech4DModelviewer." (2021).
  14. Fuster-Guilló, Andrés, Jorge Azorín-López, Marcelo Saval-Calvo, Juan Miguel Castillo-Zaragoza, Nahuel Garcia-D’Urso, and Robert B Fisher. "Rgb-d-based framework to acquire, visualize and measure the human body for dietetic treatments." Sensors (2020).

Projects

Tech4Diet Predict 2022 - Present

The main objective of this project is the generation of predictive 3D models of the shape of the human body. To achieve this, the data collected in the Tech4Diet project (3D models, clinical data, psychological data, etc.) are used.

DeepFish2 2022 - 2023

DeepFish 2 aims to improve the artificial vision prototype for identifying and sizing fish in markets, developed in the original DeepFish project. This will include expanding the target species and market types, and adding geo-referenced traceability features.

DeepFish 2021 - 2022

DeepFish is an innovation for the management of fishing data, specifically in the identification of species and their sizing in the fish market.

Tech4Diet 2019 - 2022

This project is part of the improvement of obesity treatment from a multidisciplinary approach, taking advantage of the potential of areas in full development such as 3D modeling or virtual reality, to address open problems such as psychological aspects of treatment adherence, opening opportunities both in diet and nutritional intervention, as well as in the solution of new technological challenges.

Teaching

Degree in Computer Engineering, University of Alicante
Undergraduate degree in Computer Engineering + Business Administration and Management (I2ADE), University of Alicante
Master’s Degree in Data Science, University of Alicante
Final year undergraduate project supervision, University of Alicante