José Oramas

44 papers A* 1A 4B 2C 1Journal 22Unranked 12
YearRankTypeTitle / Venue / Authors
2026 J jnl
A taxonomy of interpretation and explanation methods for capsule network architectures.
Neurocomputing
Saja Tawalbeh, José Oramas
2026 J jnl
Enhancing hyperspectral image prediction with contrastive learning in low-label regimes.
Appl. Intell.
Salma Haidar, José Oramas
2026 J jnl
TriLite: Efficient Weakly Supervised Object Localization with Universal Visual Features and Tri-Region Disentanglement.
CoRR
Arian Sabaghi, José Oramas
2025 J jnl
A beginner's approach to deep learning applied to VS and MD techniques.
J. Cheminformatics
Stijn Dhondt, José Oramas, Hans De Winter
2025 A* conf
Bilinear MLPs enable weight-based mechanistic interpretability.
ICLR
Michael T. Pearce, Thomas Dooms, Alice Rigg, José Oramas, Lee Sharkey
2025 J jnl
Compositionality Unlocks Deep Interpretable Models.
CoRR
Thomas Dooms, Ward Gauderis, Geraint A. Wiggins, José Oramas
2025 J jnl
Efficient Post-Hoc Uncertainty Calibration via Variance-Based Smoothing.
CoRR
Fabian Denoodt, José Oramas
2025 J jnl
Explainability-Driven Dimensionality Reduction for Hyperspectral Imaging.
CoRR
Salma Haidar, José Oramas
2025 J jnl
Explaining and interpreting hyperdimensional computing classifiers on tabular data.
Neurocomputing
Laura Smets, Werner Van Leekwijck, Steven Latré, José Oramas
2025 B conf
Label-Efficient Learning for Radio Frequency Fingerprint Identification.
WCNC
Thayheng Nhem, Fabian Denoodt, Maarten Weyn, Michaël Peeters, José Oramas, Rafael Berkvens
2025 — conf
Quantifying Generative Stability: Mode Collapse Entropy Score for Mode Diversity Evaluation.
WACV (Workshops)
Jens Duym, José Oramas, Ali Anwar
2025 — conf
SVEBI: Towards the Interpretation and Explanation of Spiking Neural Networks.
ECML/PKDD (3)
Jasper De Laet, Hamed Behzadi-Khormouji, Lucas Deckers, José Oramas
2025 — conf
Smooth InfoMax - Towards Easier Post-Hoc Interpretability.
ECML/PKDD (3)
Fabian Denoodt, Bart de Boer, José Oramas
2025 J jnl
Towards the characterization of representations learned via capsule-based network architectures.
Neurocomputing
Saja AL-Tawalbeh, José Oramas
2024 — conf
Deep Learning Model Compression for Resource Efficient Activity Recognition on Edge Devices: A Case Study.
VISIGRAPP (4): VISAPP
Dieter Balemans, Benjamin Vandersmissen, Jan Steckel, Siegfried Mercelis, Philippe Reiter, José Oramas
2024 J jnl
Deep Model Interpretation with Limited Data : A Coreset-based Approach.
CoRR
Hamed Behzadi-Khormouji, José Oramas
2024 J jnl
Enhancing Hyperspectral Image Prediction with Contrastive Learning in Low-Label Regime.
CoRR
Salma Haidar, José Oramas
2024 J jnl
On the coherency of quantitative evaluation of visual explanations.
Comput. Vis. Image Underst.
Benjamin Vandersmissen, José Oramas
2024 — conf
Recognizing Actions in High-Resolution Low-Framerate Videos: A Feasibility Study in the Construction Sector.
VISIGRAPP (4): VISAPP
Benjamin Vandersmissen, Arian Sabaghi, Philippe Reiter, José Oramas
2024 J jnl
Smooth InfoMax - Towards easier Post-Hoc interpretability.
CoRR
Fabian Denoodt, Bart de Boer, José Oramas
2024 J jnl
The Trifecta: Three simple techniques for training deeper Forward-Forward networks.
Trans. Mach. Learn. Res.
Thomas Dooms, Ing Jyh Tsang, José Oramas
2023 — conf
A Contrastive Learning Method for Multi-Label Predictors on Hyperspectral Images.
WHISPERS
Salma Haidar, José Oramas
2023 A conf
A Protocol for Evaluating Model Interpretation Methods from Visual Explanations.
WACV
Hamed Behzadi Khormuji, José Oramas
2023 — conf
Analyzing the Explanation and Interpretation Potential of Matrix Capsule Networks.
PKDD/ECML Workshops (1)
Andrei Bondarenko, Saja Tawalbeh, José Oramas
2023 — conf
Automated Virtual Reduction of Displaced Distal Radius Fractures.
ISBI
Jana Osstyn, Femke Danckaers, Annemieke Van Haver, José Oramas, Matthias Vanhees, Jan Sijbers
2023 J jnl
Considering Layerwise Importance in the Lottery Ticket Hypothesis.
CoRR
Benjamin Vandersmissen, José Oramas
2023 J jnl
FICNN: A Framework for the Interpretation of Deep Convolutional Neural Networks.
CoRR
Hamed Behzadi-Khormouji, José Oramas
2023 — conf
Human Motion Prediction on the IKEA-ASM Dataset.
VISIGRAPP (5: VISAPP)
Mattias Billast, Kevin Mets, Tom De Schepper, José Oramas, Steven Latré
2023 B conf
Interpreting Convolutional Neural Networks by Explaining Their Predictions.
ICIP
Toon Meynen, Hamed Behzadi-Khormouji, José Oramas
2023 J jnl
On The Coherence of Quantitative Evaluation of Visual Expalantion.
CoRR
Benjamin Vandersmissen, José Oramas
2023 J jnl
The Trifecta: Three simple techniques for training deeper Forward-Forward networks.
CoRR
Thomas Dooms, Ing Jyh Tsang, José Oramas
2023 J jnl
Towards the Characterization of Representations Learned via Capsule-based Network Architectures.
CoRR
Saja AL-Tawalbeh, José Oramas
2023 J jnl
Training Methods of Multi-Label Prediction Classifiers for Hyperspectral Remote Sensing Images.
Remote. Sens.
Salma Haidar, José Oramas
2023 J jnl
Training Methods of Multi-label Prediction Classifiers for Hyperspectral Remote Sensing Images.
CoRR
Salma Haidar, José Oramas
2022 A conf
AIMLAI: Advances in Interpretable Machine Learning and Artificial Intelligence.
CIKM
Adrien Bibal, Tassadit Bouadi, Benoît Frénay, Luis Galárraga, José Oramas
2022 — conf
Deep Set Conditioned Latent Representations for Action Recognition.
VISIGRAPP (5: VISAPP)
Akash Singh, Tom De Schepper, Kevin Mets, Peter Hellinckx, José Oramas, Steven Latré
2022 J jnl
Deep set conditioned latent representations for action recognition.
CoRR
Akash Singh, Tom De Schepper, Kevin Mets, Peter Hellinckx, José Oramas, Steven Latré
2022 C conf
Object Detection To Enable Autonomous Vessels On European Inland Waterways.
IECON
Mattias Billast, Robin Janssens, Astrid Vanneste, Simon Vanneste, Olivier Vasseur, Ali Anwar, Kevin Mets, Tom De Schepper, José Oramas, Steven Latré, Peter Hellinckx
2021 — ed.
Machine Learning and Principles and Practice of Knowledge Discovery in Databases - International Workshops of ECML PKDD 2021, Virtual Event, September 13-17, 2021, Proceedings, Part I
PKDD/ECML Workshops (1)
Michael Kamp, Irena Koprinska, Adrien Bibal, Tassadit Bouadi, Benoît Frénay, Luis Galárraga, José Oramas, Linara Adilova, Yamuna Krishnamurthy, Bo Kang, Christine Largeron, Jefrey Lijffijt, Tiphaine Viard, Pascal Welke, Massimiliano Ruocco, Erlend Aune, Claudio Gallicchio, Gregor Schiele, Franz Pernkopf, Michaela Blott, Holger Fröning, Günther Schindler, Riccardo Guidotti, Anna Monreale, Salvatore Rinzivillo, Przemyslaw Biecek, Eirini Ntoutsi, Mykola Pechenizkiy, Bodo Rosenhahn, Christopher L. Buckley, Daniela Cialfi, Pablo Lanillos, Maxwell Ramstead, Tim Verbelen, Pedro M. Ferreira, Giuseppina Andresini, Donato Malerba, Ibéria Medeiros, Philippe Fournier-Viger, M. Saqib Nawaz, Sebastián Ventura, Meng Sun, Min Zhou, Valerio Bitetta, Ilaria Bordino, Andrea Ferretti, Francesco Gullo, Giovanni Ponti, Lorenzo Severini, Rita P. Ribeiro, João Gama, Ricard Gavaldà, Lee Cooper, Naghmeh Ghazaleh, Jonas Richiardi, Damian Roqueiro, Diego Saldana Miranda, Konstantinos Sechidis, Guilherme Graça
2021 — ed.
Machine Learning and Principles and Practice of Knowledge Discovery in Databases - International Workshops of ECML PKDD 2021, Virtual Event, September 13-17, 2021, Proceedings, Part II
PKDD/ECML Workshops (2)
Michael Kamp, Irena Koprinska, Adrien Bibal, Tassadit Bouadi, Benoît Frénay, Luis Galárraga, José Oramas, Linara Adilova, Yamuna Krishnamurthy, Bo Kang, Christine Largeron, Jefrey Lijffijt, Tiphaine Viard, Pascal Welke, Massimiliano Ruocco, Erlend Aune, Claudio Gallicchio, Gregor Schiele, Franz Pernkopf, Michaela Blott, Holger Fröning, Günther Schindler, Riccardo Guidotti, Anna Monreale, Salvatore Rinzivillo, Przemyslaw Biecek, Eirini Ntoutsi, Mykola Pechenizkiy, Bodo Rosenhahn, Christopher L. Buckley, Daniela Cialfi, Pablo Lanillos, Maxwell Ramstead, Tim Verbelen, Pedro M. Ferreira, Giuseppina Andresini, Donato Malerba, Ibéria Medeiros, Philippe Fournier-Viger, M. Saqib Nawaz, Sebastián Ventura, Meng Sun, Min Zhou, Valerio Bitetta, Ilaria Bordino, Andrea Ferretti, Francesco Gullo, Giovanni Ponti, Lorenzo Severini, Rita P. Ribeiro, João Gama, Ricard Gavaldà, Lee Cooper, Naghmeh Ghazaleh, Jonas Richiardi, Damian Roqueiro, Diego Saldana Miranda, Konstantinos Sechidis, Guilherme Graça
2021 A conf
MinMaxCAM: Improving object coverage for CAM-based Weakly Supervised Object Localization.
BMVC
Kaili Wang, José Oramas, Tinne Tuytelaars
2021 — conf
Object Detection with Semi-supervised Adversarial Domain Adaptation for Real-Time Edge Devices.
BNAIC/BENELEARN
Mattias Billast, Tom De Schepper, Kevin Mets, Peter Hellinckx, José Oramas, Steven Latré
2021 — conf
Task Independent Capsule-Based Agents for Deep Q-Learning.
BNAIC/BENELEARN
Akash Singh, Tom De Schepper, Kevin Mets, Peter Hellinckx, José Oramas, Steven Latré
2020 A conf
AIMLAI'20: Third Workshop on Advances in Interpretable Machine Learning and Artificial Intelligence.
CIKM
Adrien Bibal, Tassadit Bouadi, Benoît Frénay, Luis Galárraga, José Oramas