Beatriz Remeseiro (0000-0001-9265-253X)

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Beatriz Remeseiro received the PhD degree “Cum Laude with International Honors” in Computer Science for her work on medical image analysis in 2014, at the University of A Coruña (Spain). Her PhD thesis was honored with the “2nd Award to the Best PhD Thesis 2014” from the Spanish Association for Artificial Intelligence, and with the “Gradiant Award to the best PhD Thesis applied to ICT 2016” from the Galician Official College and Association of Telecommunications Engineering. After two postdoctoral fellowships from 2015 to 2017, at the INESC TEC (Portugal) and the University of Barcelona (Spain), she is currently a tenured Associate Professor at the University of Oviedo (Spain). Her main research interests include computer vision and deep learning, mainly applied to real-world problems in areas such as medicine or industry.

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Universidad de Oviedo: Gijón, Asturias, ES

2021-12-14 to present | Tenured Associate Professor (Department of Computer Science)

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Beatriz Remeseiro

https://orcid.org/0000-0001-9265-253X

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Employment (12)

Universidad de Oviedo: Gijón, Asturias, ES

University of Oviedo: Gijón, ES

University of Barcelona: Barcelona, ES

INESC TEC - INESC Technology and Science: Porto, PT

INESC TEC - INESC Technology and Science: Porto, PT

CITIC, University of A Coruña: A Coruña, ES

University of A Coruña: A Coruña, ES

University of A Coruña: A Coruña, ES

University of A Coruña: A Coruña, ES

CITIC, University of A Coruña: A Coruña, ES

University of A Coruña: A Coruña, ES

University of A Coruña: A Coruña, ES

Education and qualifications (4)

University of A Coruña: A Coruña, ES

University of A Coruña: A Coruña, ES

University of A Coruña: A Coruña, ES

University of A Coruña: A Coruña, ES

Professional activities (3)

Universidad de Castilla-La Mancha: Ciudad Real, Castilla-La Mancha, ES

Universidade do Minho: Braga, Braga, PT

Glasgow Caledonian University: Glasgow, Glasgow, GB

Works (50 of 81)

Self-consistent Deep Approximation of Retinal Traits for Robust and Highly Efficient Vascular Phenotyping of Retinal Colour Fundus Images

Towards a Lightweight CNN for Semantic Food Segmentation

BTS U-Net: A data-driven approach to brain tumor segmentation through deep learning

A multi-task framework for breast cancer segmentation and classification in ultrasound imaging

MAPunet: High-resolution snow depth mapping through U-Net pixel-wise regression

Eye-LRCN: A Long-Term Recurrent Convolutional Network for Eye Blink Completeness Detection

Optimizing Image Feature Extraction and Selection: A Comprehensive Review with Spark Case Studies

Deep-stratification of the cardiovascular risk by ultrasound carotid artery images

A Pseudo-Label Guided Hybrid Approach for Unsupervised Domain Adaptation

All-in-one picture: visual summary of items in a recommender system

Do all roads lead to Rome? Studying distance measures in the context of machine learning

Users' photos of items can reveal their tastes in a recommender system

Users' photos of items can reveal their tastes in a recommender system

Polyvascular Subclinical Atherosclerosis: Correlation Between Ankle Brachial Index and Carotid Atherosclerosis in a Population-Based Sample

An end-to-end framework for intima media measurement and atherosclerotic plaque detection in the carotid artery

The role of feature selection in personalized recommender systems

When the best reviews are not placed between extremes

When the best reviews are not placed between extremes

Bayesian deep learning for semantic segmentation of food images

Playing to distraction: towards a robust training of CNN classifiers through visual explanation techniques

Automatic classification of retinal blood vessels based on multilevel thresholding and graph propagation

DeepNEM: Deep Network Energy-Minimization for Agricultural Field Segmentation

On the effectiveness of convolutional autoencoders on image-based personalized recommender systems

Playing to distraction: towards a robust training of CNN classifiers through visual explanation techniques

Semantic segmentation with DenseNets for carotid artery ultrasound plaque segmentation and CIMT estimation

FINEXT 2020: DESIGNING INNOVATIVE ACTIONS BASED ON PAST EXPERIENCES AND PROJECTS

ON THE IMPROVEMENT OF A PROGRAMMING GYMKHANA FOR PYTHON SELF-LEARNING

Towards explainable personalized recommendations by learning from users’ photos

Feature selection in image analysis: a survey

A review of feature selection methods in medical applications

Automatic detection of defective crankshafts by image analysis and supervised classification

A Preliminary Study of Image Analysis for Parasite Detection on Honey Bees

Feature Selection for Big Visual Data: Overview and Challenges

Grab, Pay, and Eat: Semantic Food Detection for Smart Restaurants

Machine Learning Applied to Optometry Data

Algorithmic challenges in big data analytics

Analyzing First-Person Stories Based on Socializing, Eating and Sedentary Patterns

Automatic and semi-automatic approaches for arteriolar-to-venular computation in retinal photographs

Objective Quality Assessment of Retinal Images Based on Texture Features

Parallel definition of tear film maps on distributed-memory clusters for the support of dry eye diagnosis

Acceleration of tear film map definition on multicore systems

Evaluation of an automatic dry eye test using MCDM methods and rank correlation

IDEAS: A web-based system for dry eye assessment

Machine learning for medical applications

Machine learning for medical applications

A Texture-Based Method for Choroid Segmentation in Retinal EDI-OCT Images

Automatic Eye Blink Detection Using Consumer Web Cameras

CASDES: a computer-aided system to support dry eye diagnosis based on tear film maps