rpcruz@fe.up.pt
rpmcruz
0000-0002-5189-6228
Scholar
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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.
Sources for the following metrics: • Impact Factor (IF) as reported by the journal's webpage. • SJR rank quartiles are from Scimago and best quartile is chosen when multiple categories exist. • CORE rank is from ICORE for whatever last year is available for that conference. • Citation counts come from Crossref. Last update: 2025-03-21
# | Year | Paper | Citations | IF | SJR Rank | CORE Rank | |
---|---|---|---|---|---|---|---|
1 | [SUBMITTED] R. Cruz, J. Cardoso, "Interpretable Image Classification using Object Detection", IEEE Transactions on Image Processing | journal | 10.8 | Q1 | |||
2 | [SUBMITTED] R. Cruz, "Spatial Early-Exit for Segmentation and Object Detection", Elsevier Computer Vision and Image Understanding | journal | 4.3 | Q1 | |||
3 | 2025 | J. Cardoso, R. Cruz, T. Albuquerque, "Unimodal Distributions for Ordinal Regression", IEEE Transactions on Artificial Intelligence | journal | 0 | n/a | Q1 | |
4 | 2025 | R. Cruz, R. Cristino, J. Cardoso, "Learning Ordinality in Semantic Segmentation", IEEE Access | journal | 0 | 3.4 | Q1 | |
5 | 2025 | J. Barbero-Gómez, R. Cruz, J. Cardoso, P. Gutiérrez, C. Hervás-Martínez, "CNN explanation methods for ordinal regression tasks", Elsevier Neurocomputing | journal | 0 | 5.5 | Q1 | |
6 | 2024 | A. Bezerra, I. Pereira, M. Rebelo, D. Coelho, D. Oliveira, J. Costa, R. Cruz, "A case study on phishing detection with a machine learning net", Springer International Journal of Data Science and Analytics | journal | 0 | 3.4 | Q2 | |
7 | 2024 | C. Pereira, R. Cruz, J. Fernandes, J. Pinto, J. Cardoso, "Weather and Meteorological Optical Range Classification for Autonomous Driving", IEEE Transactions on Intelligent Vehicles | journal | 1 | 14 | Q1 | |
8 | 2023 | F. Campos, F. Cerqueira, R. Cruz, J. Cardoso, "YOLOMM – You Only Look Once for Multi-modal Multi-tasking", Iberoamerican Congress on Pattern Recognition 2023 (CIARP) | conference | 0 | C | ||
9 | 2023 | D. e Silva, R. Cruz, "Condition Invariance for Autonomous Driving by Adversarial Learning", Iberoamerican Congress on Pattern Recognition 2023 (CIARP) | conference | 0 | C | ||
10 | 2023 | R. Cruz, A. Shihavuddin, M. Maruf, J. Cardoso, "Active Supervision: Human in the Loop", Iberoamerican Congress on Pattern Recognition 2023 (CIARP) | conference | 0 | C | ||
11 | 2023 | P. Serrano e Silva, R. Cruz, A. Shihavuddin, T. Gonçalves, "Interpretability-Guided Human Feedback During Neural Network Training", Iberian Conference on Pattern Recognition and Image Analysis 2023 (IbPRIA) | conference | 1 | C | ||
12 | 2023 | J. Barbero-Gómez, R. Cruz, J. Cardoso, P. Gutiérrez, C. Hervás-Martínez, "Evaluating the Performance of Explanation Methods on Ordinal Regression CNN Models", International Work-Conference on Artificial Neural Networks 2023 (IWANN) | conference | 0 | n/a | ||
13 | 2023 | R. Cruz, D. Silva, T. Gonçalves, D. Carneiro, J. Cardoso, "Two-Stage Framework for Faster Semantic Segmentation", MDPI Sensors | journal | 1 | 3.4 | Q1 | |
14 | 2023 | D. Teixeira e Silva, R. Cruz, T. Gonçalves, D. Carneiro, "Two-stage semantic segmentation in neural networks", Fifteenth International Conference on Machine Vision (ICMV 2022) | conference | 0 | C | ||
15 | 2023 | T. Albuquerque, L. Rosado, R. Cruz, M. Vasconcelos, T. Oliveira, J. Cardoso, "Rethinking low-cost microscopy workflow: Image enhancement using deep based Extended Depth of Field methods", Elsevier Intelligent Systems with Applications | journal | 0 | n/a | Q1 | |
16 | 2022 | T. Albuquerque, R. Cruz, J. Cardoso, "Quasi-Unimodal Distributions for Ordinal Classification", MDPI Mathematics | journal | 2 | 2.3 | Q2 | |
17 | 2021 | T. Albuquerque, R. Cruz, J. Cardoso, "Ordinal losses for classification of cervical cancer risk", PeerJ Computer Science | journal | 17 | 3.8 | Q1 | |
18 | 2021 | R. Cruz, R. Prates, E. Simas Filho, J. Pinto Costa, J. Cardoso, "Background Invariance by Adversarial Learning", 2020 25th International Conference on Pattern Recognition (ICPR) | conference | 1 | B | ||
19 | 2019 | R. Cruz, J. Pinto Costa, J. Cardoso, "Averse Deep Semantic Segmentation", 2019 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) | conference | 1 | C | ||
20 | 2019 | R. Prates, R. Cruz, A. Marotta, R. Ramos, E. Simas Filho, J. Cardoso, "Insulator visual non-conformity detection in overhead power distribution lines using deep learning", Elsevier Computers & Electrical Engineering | journal | 49 | 4.0 | Q1 | |
21 | 2019 | R. Cruz, J. Pinto Costa, J. Cardoso, "Automatic Augmentation by Hill Climbing", International Conference on Artificial Neural Networks 2019 (ICANN) | conference | 1 | C | ||
22 | 2018 | K. Fernandes, R. Cruz, J. Cardoso, "Deep Image Segmentation by Quality Inference", 2018 International Joint Conference on Neural Networks (IJCNN) | conference | 10 | B | ||
23 | 2018 | R. Cruz, M. Silveira, J. Cardoso, "A Class Imbalance Ordinal Method for Alzheimer’s Disease Classification", 2018 International Workshop on Pattern Recognition in Neuroimaging (PRNI) | conference | 0 | n/a | ||
24 | 2018 | R. Cruz, K. Fernandes, J. Costa, M. Ortiz, J. Cardoso, "Binary ranking for ordinal class imbalance", Springer Pattern Analysis and Applications | journal | 2 | 3.7 | Q2 | |
25 | 2017 | R. Cruz, K. Fernandes, J. Pinto Costa, J. Cardoso, "Constraining Type II Error: Building Intentionally Biased Classifiers", Springer Pattern Analysis and Applications | journal | 3 | 3.7 | Q2 | |
26 | 2017 | M. Pérez-Ortiz, K. Fernandes, R. Cruz, J. Cardoso, J. Briceño, C. Hervás-Martínez, "Fine-to-Coarse Ranking in Ordinal and Imbalanced Domains: An Application to Liver Transplantation", International Work-Conference on Artificial Neural Networks (IWANN) | conference | 1 | n/a | ||
27 | 2017 | R. Cruz, K. Fernandes, J. Pinto Costa, M. Pérez Ortiz, J. Cardoso, "Combining Ranking with Traditional Methods for Ordinal Class Imbalance", International Work-Conference on Artificial Neural Networks (IWANN) | conference | 8 | n/a | ||
28 | 2017 | R. Cruz, K. Fernandes, J. Pinto Costa, M. Ortiz, J. Cardoso, "Ordinal Class Imbalance with Ranking", Iberian Conference on Pattern Recognition and Image Analysis (IbPRIA) | conference | 5 | C | ||
29 | 2016 | R. Cruz, K. Fernandes, J. Cardoso, J. Pinto Costa, "Tackling class imbalance with ranking", 2016 International Joint Conference on Neural Networks (IJCNN) | conference | 23 | B |
# | Year | Student | Title | Institution | Observation | |
---|---|---|---|---|---|---|
1 | active | PhD Advanced Project | André Almeida Catarino | Data Marketplace for Driving Assistance Models | FEUP | |
2 | active | MSc Dissertation | Rúben Monteiro | Intelligent 3D Interaction | FEUP | (co-supervision) Main supervisor: Rui Rodrigues |
3 | active | BSc Project | Diogo Venade | How Robust are Ordinal Regression Methods against Adversarial Attacks? | FEUP | |
4 | active | BSc Project | Bruno Ferreira | Automatic Recognition of Pig Behavior | FEUP | with co-supervisor: Nuno Lavado (ISEC) |
5 | active | BSc Project | Isabel Sá | Automatic Recognition of Pig Behavior | FEUP | with co-supervisor: Nuno Lavado (ISEC) |
6 | active | MSc Dissertation | João Ricardo Ramos Alves | Self-supervised Occupancy Networks in Autonomous Driving | FEUP | Internship @ Bosch Car Multimedia (Filipe Gonçalves) |
7 | active | MSc Dissertation | Luís Paulo da Rocha Miranda | Unsupervised Active Learning: Which Frames are Most Important in Autonomous Driving? | FEUP | Internship @ Bosch Car Multimedia (Filipe Gonçalves) |
8 | active | MSc Dissertation | Bruno Vieira Dias | Trust or not to trust: When to trust the label prediction | FEUP | Internship @ Bosch Car Multimedia (Lucas Agostinho) |
9 | active | MSc Dissertation | Alexandre Ferreira Nunes | Semi-supervised Learning on 2D Projections for Autonomous Driving | FEUP | |
10 | active | MSc Dissertation | Sofía Lucía | Ordinal losses for range estimation in autonomous driving | FEUP | |
11 | 2023 Sept–2024 Feb | PhD Advanced Project | Felipe Coelho | Ensembles for Ordinal Classification | FEUP | |
12 | 2024 July | Internship | Isabel Gomes de Sá | Making Sense of Ordinal Images Without Labels | INESC TEC | |
13 | 2024 | MSc Dissertation | Diana Teixeira Silva | Quantifying How Deep 3D Representations Promote Label Efficiency | FEUP | |
14 | 2024 | MSc Dissertation | Francisco Gonçalves Cerqueira | Exploring Label Efficiency with Semi-Supervision and Self-Supervision Methods | FEUP | |
15 | 2024 | MSc Dissertation | Airton Tiago | Data Augmentation for Ordinal Data | FEUP | with co-supervisor: Jaime Cardoso |
16 | 2023 | MSc Dissertation | Alankrita Asthana | Iterative Inference for Point-Clouds | TUM | |
17 | 2023 | MSc Dissertation | Rafael Cristino | Introducing Domain Knowledge to Scene Parsing in Autonomous Driving | FEUP | with co-supervisor: Jaime Cardoso |
18 | 2023 | MSc Dissertation | José Guerra | Uncertainty-Driven Out-of-Distribution Detection in 3D LiDAR Object Detection for Autonomous Driving | FEUP | Internship @ Bosch Car Multimedia (João Teixeira) |
19 | 2022 | MSc Dissertation | Pedro Silva | Human Feedback during Neural Networks Training | FEUP | with co-supervisor: Tiago Gonçalves |
20 | 2022 | MSc Dissertation | João Silva | Environment Detection for Railway Applications based on Automotive Technology | FEUP | Internship @ Continental (António Pereira e João Figueiredo) |
21 | 2022 | MSc Dissertation | Ana Bezerra | Phishing Detection with a Machine Learning Net | FCUP | Internship @ E-Goi (Ivo Pereira) |
22 | 2024 | BSc Project | João Monteiro | Cross-vehicle collaboration using RGB cameras | FCUP | with co-supervisor: Celso Pereira |
23 | 2024 | BSc Project | Diogo Mendes | Automatic Recognition of Pig Activity in an Intensive Production System | FCUP | with co-supervisor: Nuno Lavado |
24 | 2024 | BSc Project | Beatriz Sá | Research on Deep Augmentation for Ordinal Regression | FCUP | with co-supervisor: Jaime S. Cardoso |
25 | 2024 | BSc Project | Eliandro Melo | Resource Efficiency using Deep Q-Learning in Autonomous Driving | FCUP | |
26 | 2024 | BSc Project | Ivo Duarte Simões | Resource Efficiency using PPO in Autonomous Driving | FCUP | |
27 | 2023 | BSc Project | Diana Teixeira Silva | Condition Invariance for Autonomous Driving by Adversarial Learning | FEUP | |
28 | 2022 | BSc Project | Diana Teixeira Silva | Semantic Segmentation in Neural Networks using Iterative Visual Attention | FEUP | with co-supervisor: Tiago Gonçalves |
29 | 2022 | BSc Project | Filipe Campos, Francisco Cerqueira, Vasco Alves | Mobile App using Object Detection for Car Driving | FEUP | |
30 | 2022 | BSc Project | Bruno Gomes, Rafael Camelo | Internship at ANO | FEUP |