Veronica Vilaplana
| Position | |
|---|---|
| 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, ORCID: 0000-0001-6924-9961
Scopus Author ID: 23394280500, Researcher ID: O-1726-2014, UPC Futur
Journal Articles top
| , “The mediating role of neuroimaging-derived biological brain age between risk factors for dementia and cognitive decline in middle/late-aged asymptomatic individuals: a cohort study”, The Lancet Healthy Longevity, Submitted. |
| , “Feature propagation as self-supervision signals on graphs”, Knowledge-Based Systems, Submitted. |
| , “Bcn20000: Dermoscopic lesions in the wild”, Nature - Scientific Data, vol. 11, In Press. |
| , “SurvLIMEpy: A Python package implementing SurvLIME”, Expert Systems With Applications, vol. 237, Part C, 2024. |
| , “AmodalAppleSize_RGB-D dataset: RGB-D images of apple trees annotated with modal and amodal segmentation masks for fruit detection, visibility and size estimation”, Data in Brief, vol. 52, 2024. |
Book Chapters and Bookstop
| , “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, Submitted. |
| , “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. |
| , “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. |
| , “Leishmaniasis Parasite Segmentation and Classification Using Deep Learning”, in Articulated Motion and Deformable Objects, vol. 10945, Springer International Publishing, 2018, pp. 53-62. |
| , “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. |
Conference Papers top
| , “Bridging Domains in Melanoma Diagnostics: Predicting BRAF Mutations and Sentinel Lymph Node Positivity with Attention-Based Models in Histological Images”, in IEEE/CVF Conference on Computer Vision and Pattern Recognition (DEF-AI-MIA workshop), In Press. |
| , “Unsupervised Domain Adaptation for Multi-Stain Cell Detection in Breast Cancer with Transformers”, in IEEE/CVF Conference on Computer Vision and Pattern Recognition (DEF-AI-MIA workshop), In Press. |
| , “Cell-DETR: Efficient cell detection and classification in WSIs with transformers”, in Medical Imaging with Deep Learning (MIDL 2024), In Press. |
| , “Synthesis of Prostate MRI Scans: A Comparison of StyleGAN2-ADA and Latent Diffusion Models ”, in Conferencia de la Asociación Española para la Inteligencia Artificial, IABioMed workshop, In Press. |
| , “Brain-age prediction and its associations with glial and synaptic CSF markers”, in Alzheimer's Association International Conference, Amsterdam, Netherlands, 2023. |
Theses top
| , “BIOLOGICAL BRAIN-AGE PREDICTION USING MACHINE LEARNING ON NEUROIMAGING DATA: LINKS WITH PATHOPHYSIOLOGICAL MECHANISMS, DEMENTIA RISK FACTORS AND COGNITIVE DECLINE”, 2024. |
| , “Super-resolution and semantic segmentation of remote sensing images using deep learning techniques”, 2022. |
| , “Study of early stages of Alzheimer’s disease using magnetic resonance imaging”, Universitat Politècnica de Catalunya, Barcelona, 2019. |
, “Visual Object Analysis using Regions and Local Features”, 2016. (2.5 MB) |
| , “Region-based face detection, segmentation and tracking. framework definition and application to other objects”, Universitat Politècnica de Catalunya (UPC), 2010. |
Other top
| , “Deep learning for semantic segmentation of airplane hyperspectral imaging”. 2019. | Ms Thesis |
| , “Clasificación de lesiones de piel con un ensemble de redes neuronales residuales”. 2019. | Ms Thesis |
| , “Clasificación de imágenes dermatoscópicas utilizando Redes Neuronales Convolucionales e información de metadatos”. 2019. | Ms Thesis |
| , “Synthesis of acne images for data augmentation with generative adversarial networks”. 2019. | Ms Thesis |
| , “Interpretability of Deep Learning Models”. 2019. | Ms Thesis |
Projects top
Research Areas top
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Biomedical Applications | Internal | Jan 2012 | Dec 2024 |
 |
Region-based image and video processing | Internal | Jan 1992 | Dec 2020 |
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Deep learning | Internal | Jun 2014 | Dec 2020 |
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Saliency prediction | Internal | Feb 2015 | Dec 2019 |
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Multimedia Retrieval | Internal | Sep 2001 | Dec 2018 |
Demos and Resources top
 |
Additional results for "Action Tube Extraction based 3D-CNN for RGB-D Action Recognition" | Results | May 2018 |
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VNeAT (Voxel-wise Neuroimaging Analysis Toolbox) | Software | Jun 2017 |
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Saliency Maps on Image Hierarchies | Results | May 2015 |
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Automatic Keyframe Selection over TVC database | Results | Jun 2013 |
Teaching top
| Acronym | Title | Level | College |
|---|---|---|---|
| VC | Computer Vision | Degree in Engineering of Audiovisual Systems | ESEIAAT |
| 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 |
| ICV | Introduction to Computer Vision | Master in Telecommunications Engineering (MET) | ETSETB - Telecom BCN |
| IDL | Introduction to Deep Learning | BSc | ETSETB TelecomBCN |
| IHCV | M1. Introduction to Humand and Computer Vision | Master in Computer Vision (MCV) | UAB, UOC, UPC & UPF |
| APA | Machine Learning Seminar (Aprendizaje Automático) | Degree in Telecommunications Technologies and Services Engineering | Telecom BCN - ETSETB |