Welcome to the official repository of the Tech4D Research Lab at the University of Alicante. We focus on applied research in Artificial Intelligence, particularly in areas such as machine learning and computer vision. This repository hosts resources, code, datasets, and documentation from our ongoing projects.
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13/11/2025 – 🗞️ New Publication Available
Our work “Zero-Shot Elasmobranch Classification Informed by Domain Prior Knowledge”, by Ismael Beviá-Ballesteros et al., has been published in Machine Learning and Knowledge Extraction (MAKE). -
27/10/2025 – 🗞️ New Publication Available
Comparative Study of Deep Learning Approaches for Fish Origin Classification, published in the Proceedings of IWANN 2025. -
25/03/2025 – 🗞️ First public release of the Tech4D Research Lab on GitHub!
Our official repository is now live, featuring projects on 3D recontruction, fish classification and elasmobranch detection. Stay tuned for updates!
- 📰 Featured in UA: Tres artículos aceptados en UCAMi 2025
- 📰 Featured in À Punt Mèdia: IA per evitar recaigudes en persones obeses
Garcia-d’Urso, N., Galan-Cuenca, A., Pérez-Sánchez, P. et al.
The DeepFish computer vision dataset for fish instance segmentation, classification, and size estimation.
Scientific Data 9, 287 (2022).
👉 https://doi.org/10.1038/s41597-022-01416-0
📚 Download Dataset → Available via Zenodo:
2026
- Publications coming soon.
2025
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🦈 Zero-Shot Elasmobranch Classification Informed by Domain Prior Knowledge
Ismael Beviá-Ballesteros, Mario Jerez-Tallón et al.
Machine Learning and Knowledge Extraction (MAKE).
📚 MDPI Link -
🐟 Comparative Study of Deep Learning Approaches for Fish Origin Classification
Mario Jerez-Tallón, Ismael Beviá Ballesteros et al.
Advances in Computational Intelligence (IWANN 2025).
📚 Springer Link
2024
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👩⚕️ 3D Reconstruction of the Human Body from Partial Scans Using Parametric Models
García d'Urso, Nahuel. et al. Proceedings of UCAmI 2024
📚 Springer Link -
🐟 Automatic Identification of Fish Species and Their Farmed or Wild Origin by Computer Vision and Deep Learning
Jerez, Mario. et al. Proceedings of UCAmI 2024
📚 Springer Link
| Name | Role | GitHub | Contact |
|---|---|---|---|
| Dr. Andrés Fuster Guilló | Principal Investigator | – | [email protected] |
| Dr. Jorge Azorín López | Principal Investigator | – | [email protected] |
| Dr. Marcelo Saval Calvo | Principal Investigator | – | [email protected] |
| Dr. Nahuel Emiliano Garcia d'Urso | Principal Investigator | @nawue | [email protected] |
| Bernabé Sanchez Sos | PhD Student | @Bernabe19 | [email protected] |
| Ismael Beviá Ballesteros | PhD Student | @ibevias | [email protected] |
| Mario Jerez Tallón | PhD Student | @Mariojt72 | [email protected] |
