Ricardo P. M. Cruz

Email: rpcruz@fe.up.pt

About: Ricardo P. M. Cruz is an Assistant Professor at the Faculty of Engineering of the University of Porto and a researcher at INESC TEC. His work focuses on machine learning, particularly deep learning, and computer vision. He received a B.Sc. degree in Computer Science (2012), an M.Sc. degree in Mathematical Engineering (2015), both from the University of Porto, and a Ph.D. degree in Computer Science (2021) jointly from the University of Porto, Aveiro and Minho. His topics cover transversal aspects of machine learning with applications to health and autonomous driving, detailed in over 20 publications with 100+ citations.

Publications

Year Title Type Venue Citations Impact Factor SJR Rank CORE Rank
2026 Preserving Ordinality in Diabetic Retinopathy Grading through a Distribution-Based Loss Function Conference paper Northern Lights Deep Learning Conference 2026 *
2025 Towards an Automated System for Pig Aggression Detection and Tracking Conference paper PAMDAS 2025 - International conference on Physical Asset Management and Data Science *
2025 Ordinal Methods for Monocular Depth Estimation Conference poster Portuguese Conference on Pattern Recognition (RECPAD) *
2025 CNN explanation methods for ordinal regression tasks Journal article Neurocomputing 5 6.5 Q1
2025 Learning Ordinality in Semantic Segmentation Journal article IEEE Access 2 3.6 Q1
2025 Unimodal Distributions for Ordinal Regression Journal article IEEE Transactions on Artificial Intelligence 2 n/a Q1
2024 YOLOMM – You Only Look Once for Multi-modal Multi-tasking Book chapter Iberoamerican Congress on Pattern Recognition 0 C
2024 Active Supervision: Human in the Loop Book chapter Iberoamerican Congress on Pattern Recognition 0 C
2024 Condition Invariance for Autonomous Driving by Adversarial Learning Book chapter Iberoamerican Congress on Pattern Recognition 0 C
2024 Tracking group-housed pigs and classification of aggressive behaviours’ using computer vision Conference abstract *
2024 A case study on phishing detection with a machine learning net Journal article International Journal of Data Science and Analytics 10 2.8 Q2
2024 Weather and Meteorological Optical Range Classification for Autonomous Driving Journal article IEEE Transactions on Intelligent Vehicles 6 14.3 Q1
2023 Interpretability-Guided Human Feedback During Neural Network Training Book chapter Iberian Conference on Pattern Recognition and Image Analysis 1 n/a
2023 Evaluating the Performance of Explanation Methods on Ordinal Regression CNN Models Book chapter International Work-Conference on Artificial Neural Networks 2 n/a
2023 Two-Stage Semantic Segmentation in Neural Networks Conference paper Fifteenth International Conference on Machine Vision (ICMV 2022) 0 C
2023 Two-Stage Framework for Faster Semantic Segmentation Journal article Sensors 1 n/a Q1
2023 Rethinking low-cost microscopy workflow: Image enhancement using deep based Extended Depth of Field methods Journal article Intelligent Systems with Applications 2 4.3 Q1
2023 Unimodal Distributions for Ordinal Regression Journal article CoRR *
2022 Quasi-Unimodal Distributions for Ordinal Classification Journal article MATHEMATICS 7 n/a Q2
2022 Deep learning-based system for real-time behavior recognition and closed-loop control of behavioral mazes using depth sensing Preprint 3
2021 Background Invariance by Adversarial Learning Conference paper 2020 25th International Conference on Pattern Recognition (ICPR) 1 B
2021 Ordinal losses for classification of cervical cancer risk Journal article PEERJ COMPUTER SCIENCE 29 2.5 Q1
2020 Correction to: Interpretable and Annotation-Efficient Learning for Medical Image Computing Book chapter International Workshop on Interpretability of Machine Intelligence in Medical Image Computing 2 n/a
2019 Automatic Augmentation by Hill Climbing Book chapter International Conference on Artificial Neural Networks 1 C
2019 Averse Deep Semantic Segmentation Conference paper 2019 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) 1 C
2019 Insulator visual non-conformity detection in overhead power distribution lines using deep learning Journal article Computers & Electrical Engineering 56 4.9 Q1
2018 A Class Imbalance Ordinal Method for Alzheimer's Disease Classification Conference paper 2018 International Workshop on Pattern Recognition in Neuroimaging (PRNI) 0 n/a
2018 Deep Image Segmentation by Quality Inference Conference paper 2018 International Joint Conference on Neural Networks (IJCNN) 10 B
2018 Binary ranking for ordinal class imbalance Journal article Pattern Analysis and Applications 2 2.0 Q2
2017 Fine-to-coarse ranking in ordinal and imbalanced domains: An application to liver transplantation Book International Work-Conference on Artificial Neural Networks (IWANN) 2 n/a
2017 Combining ranking with traditional methods for ordinal class imbalance Book International Work-Conference on Artificial Neural Networks (IWANN) 8 n/a
2017 Constraining type II error: Building intentionally biased classifiers Book International Work-Conference on Artificial Neural Networks (IWANN) 3 n/a
2017 Ordinal class imbalance with ranking Book Iberian Conference on Pattern Recognition and Image Analysis (IbPRIA) 5 n/a
2016 Tackling class imbalance with ranking Conference paper 2016 International Joint Conference on Neural Networks (IJCNN) 25 B

* National conferences, not indexed.

Master's Supervisions

Year Student Title Role Institution
2025–2026 Rodrigo André Carvalho Póvoa Automated Dressing Saturation Analysis Co-supervisor Universidade do Porto Faculdade de Engenharia
2025–2026 Diogo Miranda de Figueiredo Sarmento Object Insertion for Perception in Autonomous Driving Supervisor Universidade do Porto Faculdade de Engenharia
2025–2026 Miguel Jorge Medeiros Garrido Quantification and Qualification of Microglia Movements Supervisor Universidade do Porto Faculdade de Engenharia
2025–2026 Pedro Miguel Meruge Ferreira AI-based Diagnostic Tool of Primary Ciliary Dyskinesia Supervisor Universidade do Porto Faculdade de Engenharia
2024–2025 Alexandre Ferreira Nunes From Classification to Detection: Adapting Semi-Supervised Frameworks to Object Detection Supervisor Universidade do Porto Faculdade de Engenharia
2024–2025 Rúben Lourinha Monteiro Multimodal Modular Neural Network Frameworks for VR Interaction: a Comparative Study Co-supervisor Universidade do Porto Faculdade de Engenharia
2024–2025 Luís Paulo da Rocha Miranda Unsupervised Active Learning: Which Frames are Most Important in Autonomous Driving? Supervisor Universidade do Porto Faculdade de Engenharia
2024–2025 João Ricardo Ramos Alves Self-supervised Occupancy Networks in Autonomous Driving Supervisor Universidade do Porto Faculdade de Engenharia
2024–2025 Bruno Vieira Dias Beyond Confidence Thresholds: Pseudo-Label Selection Strategies for Semi-Supervised Learning Supervisor Universidade do Porto Faculdade de Engenharia
2024–2025 Sofía Lucía Ordinal losses for range estimation in autonomous driving Supervisor Universidade do Porto Faculdade de Engenharia
2023–2024 Diana Teixeira Silva Quantifying How Deep Implicit Representations Promote Label Efficiency Supervisor Universidade do Porto Faculdade de Engenharia
2023–2024 Francisco Gonçalves Cerqueira Exploring Label Efficiency with Semi-Supervision and Self-Supervision Methods Supervisor Universidade do Porto Faculdade de Engenharia
2023–2024 Airton Tiago Data Augmentation for Ordinal Data Supervisor Universidade do Porto Faculdade de Engenharia
2022–2023 Rafael Valente Cristino Introducing Domain Knowledge to Scene Parsing in Autonomous Driving Supervisor Universidade do Porto Faculdade de Engenharia
2022–2023 José António Barbosa da Fonseca Guerra Uncertainty-Driven Out-of-Distribution Detection in 3D LiDAR Object Detection for Autonomous Driving (internship at Bosch Car Multimedia) Supervisor Universidade do Porto Faculdade de Engenharia
2021–2022 Ana Bezerra Phishing Detection with a Machine Learning Net (internship at E-goi) Supervisor Universidade do Porto Faculdade de Ciências
2021–2022 Pedro Silva Pedro João Cruz Serrano e Silva Human Feedback during Neural Networks Training Supervisor Universidade do Porto Faculdade de Engenharia
2021–2022 João Malheiro Baptista Marcos da Silva Environment Detection for Railway Applications based on Automotive Technology (internship at Continental) Supervisor Universidade do Porto Faculdade de Engenharia