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João Manuel R. S. Tavares

João Manuel R. S. Tavares

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Computer Science
Portugal
2026

D-Index & Metrics

Computer Science

D-Index
54
Citations
13254
World Ranking
4522
National Ranking
8

Research.com Recognitions

  • 2026 - Research.com Computer Science in Portugal Leader Award
  • 2025 - Research.com Computer Science in Portugal Leader Award
  • 2023 - Research.com Computer Science in Portugal Leader Award
  • 2022 - Research.com Computer Science in Portugal Leader Award

Overview

João Manuel R. S. Tavares is a researcher affiliated with the University of Porto in Portugal. Their work spans multiple domains primarily within computer science, engineering, and medicine, contributing significantly to interdisciplinary fields that combine advanced computational methods with practical applications in healthcare and biomechanics.

Their research focuses on several main fields, including:

  • Computer Science
  • Engineering
  • Medicine

Within these, their subfields of expertise include:

  • Computer Vision and Pattern Recognition
  • Biomedical Engineering
  • Artificial Intelligence
  • Radiology, Nuclear Medicine and Imaging
  • Signal Processing

The main topics explored in their publications reflect specific technological and methodological interests:

  • Human Pose and Action Recognition
  • Gait Recognition and Analysis
  • Music and Audio Processing
  • Advanced Neural Network Applications
  • Medical Image Segmentation Techniques
  • Video Surveillance and Tracking Methods
  • Advanced X-ray and CT Imaging

João Manuel R. S. Tavares has contributed to numerous recent papers including:

  • "A multi-head attention-based transformer model for traffic flow forecasting with a comparative analysis to recurrent neural networks," 2022, Expert Systems with Applications
  • "A multilevel paradigm for deep convolutional neural network features selection with an application to human gait recognition," 2020, Expert Systems
  • "Explainable Deep Learning for Personalized Age Prediction With Brain Morphology," 2021, Frontiers in Neuroscience
  • "Alzheimer's diagnosis using deep learning in segmenting and classifying 3D brain MR images," 2020, International Journal of Neuroscience
  • "A Hybrid WD-EEMD sEMG Feature Extraction Technique for Lower Limb Activity Recognition," 2021, IEEE Sensors Journal

Frequent co-authors collaborating with Tavares include:

  • José J. M. Machado
  • Abdorreza Alavi Gharahbagh
  • Vahid Hajihashemi
  • Marta Campos Ferreira
  • Selim Reza

The venues where their work is most frequently published demonstrate a focus on sensors, applied sciences, computational biomechanics, and multimedia applications:

  • Sensors
  • Applied Sciences
  • Computer Methods in Biomechanics and Biomedical Engineering Imaging & Visualization
  • Multimedia Tools and Applications
  • Revista de Ciência Elementar

João Manuel R. S. Tavares has authored books published across several major publishers, reflecting contributions to fields such as data mining, computer vision, artificial intelligence, and expert applications. Notable publishers include Springer International Publishing, Springer Nature, and Springer Science+Business Media. Examples of book titles include:

  • Emerging Technologies in Data Mining and Information Security (2021)
  • Next Generation of Internet of Things (2022)
  • Computer Methods, Imaging and Visualization in Biomechanics and Biomedical Engineering (2020)
  • Computational Vision and Bio-Inspired Computing (2020, 2021, 2022)
  • Advances in Gait-Based Identification (2025)

Best Publications

  • Medical image registration: a review.

    Francisco P.M. Oliveira;João Manuel R.S. Tavares

  • Deep Learning in Medical Image Analysis and Multimodal Learning for Clinical Decision Support

    M. Jorge Cardoso;Tal Arbel;Gustavo Carneiro;Tanveer Syeda-Mahmood

  • A review of algorithms for medical image segmentation and their applications to the female pelvic cavity

    Zhen Ma;João Manuel R.S. Tavares;Renato Natal Jorge;T. Mascarenhas

  • Deep-learning framework to detect lung abnormality - A study with chest X-Ray and lung CT scan images

    Abhir Bhandary;G. Ananth Prabhu;V. Rajinikanth;K. Palani Thanaraj

  • Efficient supervised optimum-path forest classification for large datasets

    JoãO P. Papa;Alexandre X. FalcãO;Victor Hugo C. De Albuquerque;JoãO Manuel R. S. Tavares

  • Computational methods for the image segmentation of pigmented skin lesions

    Roberta B. Oliveira;Mercedes E. Filho;Zhen Ma;João P. Papa

  • Automatic 3D pulmonary nodule detection in CT images

    Igor Rafael S. Valente;Paulo César Cortez;Edson Cavalcanti Neto;José Marques Soares

  • Delamination analysis of carbon fibre reinforced laminates: Evaluation of a special step drill

    António T. Marques;Luís M. Durão;António G. Magalhães;João Francisco Silva

  • Deep Learning in Medical Image Analysis and Multimodal Learning for Clinical Decision Support : 4th International Workshop, DLMIA 2018, and 8th International Workshop, ML-CDS 2018, Held in Conjunction with MICCAI 2018, Granada, Spain, September 20, 2018, Proceedings

    Danail Stoyanov;Zeike Taylor;Gustavo Carneiro;Tanveer Syeda-Mahmood

  • Medical cyber-physical systems: A survey.

    Nilanjan Dey;Amira S. Ashour;Fuqian Shi;Simon James Fong

  • A medical records managing and securing blockchain based system supported by a Genetic Algorithm and Discrete Wavelet Transform

    Ahmed Faeq Hussein;N Arunkumar;Gustavo Ramírez-González;Enas W. Abdulhay

  • Computational methods for pigmented skin lesion classification in images: review and future trends

    Roberta B. Oliveira;João P. Papa;Aledir S. Pereira;João Manuel Tavares

  • A Novel Approach to Segment Skin Lesions in Dermoscopic Images Based on a Deformable Model

    Zhen Ma;Joao Manuel R. S. Tavares

  • Deep Learning and Data Labeling for Medical Applications

    Gustavo Carneiro;Diana Mateus;Loïc Peter;Andrew Bradley

  • Machine Learning in Software Defined Networks: Data collection and traffic classification

    Pedro Amaral;Joao Dinis;Paulo Pinto;Luis Bernardo

  • Social Group Optimization Supported Segmentation and Evaluation of Skin Melanoma Images

    Nilanjan Dey;Venkatesan Rajinikanth;Amira S. Ashour;João Manuel R. S. Tavares

  • Evaluation of multilayer perceptron and self-organizing map neural network topologies applied on microstructure segmentation from metallographic images

    Victor Hugo C. de Albuquerque;Auzuir Ripardo de Alexandria;Paulo César Cortez;João Manuel R.S. Tavares

  • A REVIEW ON THE CURRENT SEGMENTATION ALGORITHMS FOR MEDICAL IMAGES

    Zhen Ma;João Manuel R. S. Tavares;R. M. Natal Jorge

  • Parameter Optimization for Local Polynomial Approximation based Intersection Confidence Interval Filter Using Genetic Algorithm: An Application for Brain MRI Image De-Noising

    Nilanjan Dey;Amira S. Ashour;Samsad Beagum;Dimitra Sifaki Pistola

  • A computational approach for detecting pigmented skin lesions in macroscopic images

    Roberta B. Oliveira;Norian Marranghello;Aledir S. Pereira;João Manuel R.S. Tavares

  • Novel and powerful 3D adaptive crisp active contour method applied in the segmentation of CT lung images.

    Pedro Pedrosa Rebouças Filho;Paulo César Cortez;Antônio Carlos da Silva Barros;Victor Hugo C. de Albuquerque

Frequent Co-Authors

Victor Hugo C. de Albuquerque
Victor Hugo C. de Albuquerque Universidade Federal do Ceará
Renato Natal Jorge
Renato Natal Jorge University of Porto
João Paulo Papa
João Paulo Papa Sao Paulo State University
Nilanjan Dey
Nilanjan Dey Techno International New Town
Pedro Pedrosa Rebouças Filho
Pedro Pedrosa Rebouças Filho Instituto Federal do Ceará
Amira S. Ashour
Amira S. Ashour Tanta University
Alexandre X. Falcão
Alexandre X. Falcão State University of Campinas
Ângela Fernandes
Ângela Fernandes Polytechnic Institute of Bragança
Gustavo Carneiro
Gustavo Carneiro University of Surrey
Andrew P. Bradley
Andrew P. Bradley Queensland University of Technology

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