ricardo.pdm.cruz@gmail.com rpmcruz 0000-0002-5189-6228 PDF
Ricardo Cruz has worked on a wide range of machine learning topics, with particular emphasis on theoretical aspects of deep learning and computer vision – with 20+ publications and 100+ citations in such topics as: • adapting ranking models for class imbalance; • making convolutional neural networks invariant to background; • making them faster by adjusting the computational effort to each image; • losses for ordinal regression. He is a Post-doc Researcher on autonomous driving at the Faculty of Engineering, University of Porto, and he has been a researcher at INESC TEC since 2015, where his research earned him the computer science PhD in 2021. He has a BSc in computer science and a MSc in applied mathematics. He has frequently been an invited professor at the Faculty of Engineering, University of Porto, where he earned a pedagogic award.
Google Scholar | Scopus | Web of Science |
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7 | 5 | 4 |
Sources for the following metrics: • Impact Factor (IF) as reported by the journal's webpage. • SJR rank quartiles are from Scimago and relate to the subject category closest to machine learning (not necessarily the best quartile). • CORE rank is from ICORE for whatever last year is available for that conference. • Citation counts come from Crossref. Last update: 2024-11-09
# | Year | Paper | Citations | IF | SJR Rank | CORE Rank | |
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1 | 2024 | [ACCEPTED] J. Barbero-Gómez, R. Cruz, J. Cardoso, P. Gutiérrez, C. Hervás-Martínez, "CNN Explanation Methods for Ordinal Regression Tasks", Elsevier Neurocomputing | journal | 5.5 | Q1 | ||
2 | 2024 | [3RD ROUND] J. Cardoso, T. Albuquerque, R. Cruz, "Unimodal Distributions for Ordinal Regression", IEEE Transactions on Artificial Intelligence | journal | n/a | Q1 | ||
3 | 2024 | [2ND ROUND] R. Cristino, R. Cruz, J. Cardoso, "Learning Ordinality in Semantic Segmentation", IEEE Access | journal | 3.4 | Q1 | ||
4 | 2024 | [SUBMITTED] D. Teixeira, R. Cruz, "Quantifying How Deep 3D Representations Promote Label Efficiency", Elsevier Neurocomputing | journal | 5.5 | Q1 | ||
5 | 2024 | [SUBMITTED] R. Cruz, J. Cardoso, "Navigating the Landscape of Deep Ordinal Methods: An In-Depth Review", IEEE Transactions on Neural Networks and Learning Systems | journal | 10.2 | 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 | Q2 | |
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 | n/a | ||
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 | 15 | 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 | 47 | 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", Lecture Notes in Computer Science | conference | 3 | B | ||
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", Lecture Notes in Computer Science | conference | 1 | B | ||
27 | 2017 | R. Cruz, K. Fernandes, J. Pinto Costa, M. Pérez Ortiz, J. Cardoso, "Combining Ranking with Traditional Methods for Ordinal Class Imbalance", Lecture Notes in Computer Science | conference | 8 | B | ||
28 | 2017 | R. Cruz, K. Fernandes, J. Pinto Costa, M. Ortiz, J. Cardoso, "Ordinal Class Imbalance with Ranking", Lecture Notes in Computer Science | conference | 5 | B | ||
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 |