Florentino Fdez-Riverola

Professor

Universidade de Vigo

Spain

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Professor Florentino Fdez-Riverola is a faculty member at Universidade de Vigo, Spain. His research interests encompass areas such as machine learning applications in health and environmental sciences, urban development, and computer-aided detection systems. Recent publications include work on bibliometric reviews, pollen tracking via social media, and collaborative inference methods for neural networks.

Articles (17)

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2025

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2022

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2022

Collaborators (12)

Jorge Ribeiro

Professor

Instituto Politécnico de Leiria

PORTUGAL

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Miguel Reboiro-Jato

Associate Professor (Profesor Titular de Universidad)

Universidade de Vigo

SPAIN

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Daniel Glez-Peña

Associate Professor

Universidade de Vigo

SPAIN

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Henrique Vicente

Assistant Professor

University of Évora

PORTUGAL

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Francisco Javier Rodríguez-Rajo

Universidade de Vigo

SPAIN

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Reyes Pavon

Universidade de Vigo

SPAIN

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Maria Natália Dias Soeiro Cordeiro

Associate Professor

Universidade do Porto Faculdade de Engenharia

PORTUGAL

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Anália Lourenço

Universidade de Vigo

SPAIN

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Martín Pérez Pérez

PhD Assistant Professor

Universidade de Vigo - Campus Ourense

SPAIN

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Ivan Rodriguez-Conde

Assistant Professor

University of Arkansas at Little Rock

UNITED STATES

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Gilberto Igrejas

Universidade de Trás-os-Montes e Alto Douro

PORTUGAL

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José Ramón Méndez Reboredo

Associate Professor

Universidade de Vigo

SPAIN

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Florentino Fdez-Riverola

Research Interests

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Articles (17)

PolyDeep Advance 1: Clinical Validation of a Computer-Aided Detection System for Colorectal Polyp Detection with a Second Observer Design

Insights into wheat science: A bibliometric review using unsupervised machine learning techniques

Encouraging Eco-Innovative Urban Development

Tracking the spread of Pollen in social media: A retrospective analysis of pollen messages from Twitter (Preprint)

Horizontally Distributed Inference of Deep Neural Networks for AI-Enabled IoT

Alnus Airborne Pollen Trends during the Last 26 Years for Improving Machine Learning-Based Forecasting Methods

MOZART, a QSAR Multi-Target Web-Based Tool to Predict Multiple Drug–Enzyme Interactions

Cloud-assisted collaborative inference of convolutional neural networks for vision tasks on resource-constrained devices

A novel gluten knowledge base of potential biomedical and health-related interactions extracted from the literature: Using machine learning and graph analysis methodologies to reconstruct the bibliome

Targeted depletion of <i>pks</i>+ bacteria from a fecal microbiota using specific antibodies

Optimized convolutional neural network architectures for efficient on-device vision-based object detection

Use Social Media Knowledge for Exploring the Portuguese Wine Industry: Following Talks and Perceptions?

Boosting biomedical document classification through the use of domain entity recognizers and semantic ontologies for document representation: The case of gluten bibliome

A deep learning relation extraction approach to support a biomedical semi-automatic curation task: The case of the gluten bibliome

An Entropic Approach to Burnout in the Management of a Kitchen Staff Team

Enhancing sepsis management through machine learning techniques: A review

Real-time polyp detection model using convolutional neural networks

Collaborators (12)

Jorge Ribeiro

Miguel Reboiro-Jato

Daniel Glez-Peña

Henrique Vicente

Francisco Javier Rodríguez-Rajo

Reyes Pavon

Maria Natália Dias Soeiro Cordeiro

Anália Lourenço

Martín Pérez Pérez

Ivan Rodriguez-Conde

Gilberto Igrejas

José Ramón Méndez Reboredo

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