Veronica Vilaplana

Positionsort ascending e-mail
Associate Professor veronica.vilaplana@upc.edu
Office Phone
CN: D5-118 / ESEIAAT: TR2-102 +34 934 017 052
+34 937 398 979

Biography

Veronica Vilaplana holds a MSc degree in Mathematics and a MSc degree in Computer Sciences from the Universidad de Buenos Aires (Argentina), and a PhD in Signal Theory and Communications from the Universitat Politècnica de Catalunya (UPC). Since 2002 she is associate professor at the Department of Signal Theory and Communications (UPC). Her current research interests focus on deep learning and other machine learning models for biomedical and remote sensing applications. 

Scientific IDs:

Google Scholar,     ORCID0000-0001-6924-9961
Scopus Author ID: 23394280500,     Researcher ID: O-1726-2014,     UPC Futur 

LinkedIn,      ResearchGate

Book Chapters and Bookstop

2024
C. Hernandez, Pachón-García, C., Delicado, P., and Vilaplana, V., Interpreting Machine Learning Models for Survival Analysis: A Study of Cutaneous Melanoma Using the SEER Database, in Explainable Artificial Intelligence and Process Mining Applications for Healthcare,, vol. 2020, Springer, Cham, 2024.
2021
L. Mora and Vilaplana, V., MRI brain tumor segmentation and uncertainty estimation using 3D-UNet architectures, in Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries. BrainLes 2020, vol. 12658, Springer International Publishing, 2021, pp. 376-390.
2018
M. Combalia and Vilaplana, V., Monte-Carlo Sampling Applied to Multiple Instance Learning for Histological Image Classification, in Deep Learning in Medical Image Analysis and Multimodal Learning for Clinical Decision Support, Springer International Publishing, 2018, pp. 274-281.
M. Górriz, Aparicio, A., Raventós, B., Vilaplana, V., Sayrol, E., and López-Codina, D., Leishmaniasis Parasite Segmentation and Classification Using Deep Learning, in Articulated Motion and Deformable Objects, vol. 10945, Springer International Publishing, 2018, pp. 53-62.
A. Casamitjana, Vilaplana, V., Petrone, P., Molinuevo, J. Luis, and Gispert, J. D., Shared Latent Structures Between Imaging Features and Biomarkers in Early Stages of Alzheimer’s Disease, in PRedictive Intelligence in MEdicine, vol. 11121, Springer International Publishing, 2018, pp. 60-67.

Research Areas top

Biomedical Applications Internal Jan
2012
Dec
2024
Region-based image and video processing Internal Jan
1992
Dec
2020
Deep learning Internal Jun
2014
Dec
2020
Saliency prediction Internal Feb
2015
Dec
2019
Multimedia Retrieval Internal Sep
2001
Dec
2018

Teaching top

Acronym Title Level College
CVDL Computer Vision with Deep Learning Master in Telecommunications Engineering (MET) ETSETB - Telecom BCN
DLAI Deep Learning for Artificial Intelligence Masters MET, MATT ETSETB TelecomBCN
PDI Digtal Image Processing Degree in Engineering of Audiovisual Systems Escola d'Enginyeria de Terrassa, EET
IPSAV Introduction to Audiovisual Signal Processing Degree in Engineering of Audiovisual Systems TelecomBCN, ETSETB
APA Machine Learning Seminar (Aprendizaje Automático) Degree in Telecommunications Technologies and Services Engineering Telecom BCN - ETSETB