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José Oramas M.
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- affiliation: Catholic University of Leuven, Belgium
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2020 – today
- 2024
- [j8]Benjamin Vandersmissen, José Oramas:
On the coherency of quantitative evaluation of visual explanations. Comput. Vis. Image Underst. 241: 103934 (2024) - [j7]Yuqing Yang, Boris Joukovsky, José Oramas Mogrovejo, Tinne Tuytelaars, Nikos Deligiannis:
SNIPPET: A Framework for Subjective Evaluation of Visual Explanations Applied to DeepFake Detection. ACM Trans. Multim. Comput. Commun. Appl. 20(8): 253:1-253:29 (2024) - [c32]Dieter Balemans, Benjamin Vandersmissen, Jan Steckel, Siegfried Mercelis, Philippe Reiter, José Oramas:
Deep Learning Model Compression for Resource Efficient Activity Recognition on Edge Devices: A Case Study. VISIGRAPP (4): VISAPP 2024: 575-584 - [c31]Benjamin Vandersmissen, Arian Sabaghi, Philippe Reiter, José Oramas:
Recognizing Actions in High-Resolution Low-Framerate Videos: A Feasibility Study in the Construction Sector. VISIGRAPP (4): VISAPP 2024: 593-600 - [i22]Fabian Denoodt, Bart de Boer, José Oramas:
Smooth InfoMax - Towards easier Post-Hoc interpretability. CoRR abs/2408.12936 (2024) - [i21]Hamed Behzadi-Khormouji, José Oramas:
Deep Model Interpretation with Limited Data : A Coreset-based Approach. CoRR abs/2410.00524 (2024) - 2023
- [j6]Salma Haidar, José Oramas:
Training Methods of Multi-Label Prediction Classifiers for Hyperspectral Remote Sensing Images. Remote. Sens. 15(24): 5656 (2023) - [c30]Toon Meynen, Hamed Behzadi-Khormouji, José Oramas:
Interpreting Convolutional Neural Networks by Explaining Their Predictions. ICIP 2023: 1685-1689 - [c29]Jana Osstyn, Femke Danckaers, Annemieke Van Haver, José Oramas, Matthias Vanhees, Jan Sijbers:
Automated Virtual Reduction of Displaced Distal Radius Fractures. ISBI 2023: 1-4 - [c28]Mattias Billast, Kevin Mets, Tom De Schepper, José Oramas, Steven Latré:
Human Motion Prediction on the IKEA-ASM Dataset. VISIGRAPP (5: VISAPP) 2023: 906-914 - [c27]Hamed Behzadi Khormuji, José Oramas:
A Protocol for Evaluating Model Interpretation Methods from Visual Explanations. WACV 2023: 1421-1429 - [c26]Salma Haidar, José Oramas:
A Contrastive Learning Method for Multi-Label Predictors on Hyperspectral Images. WHISPERS 2023: 1-5 - [i20]Salma Haidar, José Oramas:
Training Methods of Multi-label Prediction Classifiers for Hyperspectral Remote Sensing Images. CoRR abs/2301.06874 (2023) - [i19]Benjamin Vandersmissen, José Oramas:
On The Coherence of Quantitative Evaluation of Visual Expalantion. CoRR abs/2302.10764 (2023) - [i18]Benjamin Vandersmissen, José Oramas:
Considering Layerwise Importance in the Lottery Ticket Hypothesis. CoRR abs/2302.11244 (2023) - [i17]Saja AL-Tawalbeh, José Oramas:
Towards the Characterization of Representations Learned via Capsule-based Network Architectures. CoRR abs/2305.05349 (2023) - [i16]Hamed Behzadi-Khormouji, José Oramas:
FICNN: A Framework for the Interpretation of Deep Convolutional Neural Networks. CoRR abs/2305.10121 (2023) - [i15]Thomas Dooms, Ing Jyh Tsang, José Oramas:
The Trifecta: Three simple techniques for training deeper Forward-Forward networks. CoRR abs/2311.18130 (2023) - 2022
- [c25]Adrien Bibal, Tassadit Bouadi, Benoît Frénay, Luis Galárraga, José Oramas:
AIMLAI: Advances in Interpretable Machine Learning and Artificial Intelligence. CIKM 2022: 5160 - [c24]Mattias Billast, Robin Janssens, Astrid Vanneste, Simon Vanneste, Olivier Vasseur, Ali Anwar, Kevin Mets, Tom De Schepper, José Oramas, Steven Latré, Peter Hellinckx:
Object Detection To Enable Autonomous Vessels On European Inland Waterways. IECON 2022: 1-6 - [c23]Akash Singh, Tom De Schepper, Kevin Mets, Peter Hellinckx, José Oramas, Steven Latré:
Deep Set Conditioned Latent Representations for Action Recognition. VISIGRAPP (5: VISAPP) 2022: 456-466 - [i14]Akash Singh, Tom De Schepper, Kevin Mets, Peter Hellinckx, José Oramas, Steven Latré:
Deep set conditioned latent representations for action recognition. CoRR abs/2212.11030 (2022) - 2021
- [c22]Kaili Wang, José Oramas, Tinne Tuytelaars:
MinMaxCAM: Improving object coverage for CAM-based Weakly Supervised Object Localization. BMVC 2021: 238 - [c21]Akash Singh, Tom De Schepper, Kevin Mets, Peter Hellinckx, José Oramas, Steven Latré:
Task Independent Capsule-Based Agents for Deep Q-Learning. BNAIC/BENELEARN 2021: 69-85 - [c20]Mattias Billast, Tom De Schepper, Kevin Mets, Peter Hellinckx, José Oramas, Steven Latré:
Object Detection with Semi-supervised Adversarial Domain Adaptation for Real-Time Edge Devices. BNAIC/BENELEARN 2021: 86-102 - [e2]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 A. D. Cooper, Naghmeh Ghazaleh, Jonas Richiardi, Damian Roqueiro, Diego Saldana Miranda, Konstantinos Sechidis, Guilherme Graça:
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. Communications in Computer and Information Science 1524, Springer 2021, ISBN 978-3-030-93735-5 [contents] - [e1]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 A. D. Cooper, Naghmeh Ghazaleh, Jonas Richiardi, Damian Roqueiro, Diego Saldana Miranda, Konstantinos Sechidis, Guilherme Graça:
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. Communications in Computer and Information Science 1525, Springer 2021, ISBN 978-3-030-93732-4 [contents] - [i13]Kaili Wang, José Oramas M., Tinne Tuytelaars:
Towards Human-Understandable Visual Explanations: Imperceptible High-frequency Cues Can Better Be Removed. CoRR abs/2104.07954 (2021) - [i12]Kaili Wang, José Oramas M., Tinne Tuytelaars:
MinMaxCAM: Improving object coverage for CAM-basedWeakly Supervised Object Localization. CoRR abs/2104.14375 (2021) - 2020
- [c19]Kaili Wang, José Oramas M., Tinne Tuytelaars:
Multiple Exemplars-Based Hallucination for Face Super-Resolution and Editing. ACCV (5) 2020: 258-273 - [c18]Kaili Wang, José Oramas M., Tinne Tuytelaars:
In Defense of LSTMs for Addressing Multiple Instance Learning Problems. ACCV (6) 2020: 444-460 - [c17]Adrien Bibal, Tassadit Bouadi, Benoît Frénay, Luis Galárraga, José Oramas:
AIMLAI'20: Third Workshop on Advances in Interpretable Machine Learning and Artificial Intelligence. CIKM 2020: 3529-3530 - [c16]Kaili Wang, Liqian Ma, José Oramas M., Luc Van Gool, Tinne Tuytelaars:
Unpaired Image-To-Image Shape Translation Across Fashion Data. ICIP 2020: 206-210 - [i11]Kaili Wang, José Oramas M., Tinne Tuytelaars:
Multiple Exemplars-based Hallucinationfor Face Super-resolution and Editing. CoRR abs/2009.07827 (2020) - [i10]Roger Granda, Tinne Tuytelaars, José Oramas M.:
Can the state of relevant neurons in a deep neural networks serve as indicators for detecting adversarial attacks? CoRR abs/2010.15974 (2020)
2010 – 2019
- 2019
- [c15]Kevin Bardool, Tinne Tuytelaars, José Oramas M.:
A Context Aware Deep Learning Architecture for Object Detection. BNAIC/BENELEARN 2019 - [c14]Kevin Bardool, Tinne Tuytelaars, José Oramas M.:
A Systematic Analysis of a Context Aware Deep Learning Architecture for Object Detection. BNAIC/BENELEARN 2019 - [c13]José Oramas M., Kaili Wang, Tinne Tuytelaars:
Interpreting and Explaining Deep Models Visually. BNAIC/BENELEARN 2019 - [c12]Lies Bollens, Tinne Tuytelaars, José Oramas M.:
Towards Object Shape Translation Through Unsupervised Generative Deep Models. ICIP 2019: 4220-4224 - [c11]José Oramas M., Kaili Wang, Tinne Tuytelaars:
Visual Explanation by Interpretation: Improving Visual Feedback Capabilities of Deep Neural Networks. ICLR (Poster) 2019 - [i9]Kaili Wang, José Oramas M., Tinne Tuytelaars:
An Iterative Approach for Multiple Instance Learning Problems. CoRR abs/1909.05690 (2019) - 2018
- [c10]Jonas Heylen, Seppe Iven, Bert De Brabandere, José Oramas M., Luc Van Gool, Tinne Tuytelaars:
From Pixels to Actions: Learning to Drive a Car with Deep Neural Networks. WACV 2018: 606-615 - [c9]Kaili Wang, Yu-Hui Huang, José Oramas M., Luc Van Gool, Tinne Tuytelaars:
An Analysis of Human-Centered Geolocation. WACV 2018: 2058-2066 - [i8]Kaili Wang, Liqian Ma, José Oramas M., Luc Van Gool, Tinne Tuytelaars:
Integrated unpaired appearance-preserving shape translation across domains. CoRR abs/1812.02134 (2018) - 2017
- [j5]José Oramas M., Luc De Raedt, Tinne Tuytelaars:
Context-based object viewpoint estimation: A 2D relational approach. Comput. Vis. Image Underst. 160: 100-113 (2017) - [j4]Basura Fernando, Efstratios Gavves, José Oramas Mogrovejo, Amir Ghodrati, Tinne Tuytelaars:
Rank Pooling for Action Recognition. IEEE Trans. Pattern Anal. Mach. Intell. 39(4): 773-787 (2017) - [i7]José Oramas M., Luc De Raedt, Tinne Tuytelaars:
Context-based Object Viewpoint Estimation: A 2D Relational Approach. CoRR abs/1704.06610 (2017) - [i6]Kaili Wang, Yu-Hui Huang, Luc Van Gool, José Oramas M., Tinne Tuytelaars:
An Analysis of Human-centered Geolocation. CoRR abs/1707.02905 (2017) - [i5]José Oramas M., Kaili Wang, Tinne Tuytelaars:
Visual Explanation by Interpretation: Improving Visual Feedback Capabilities of Deep Neural Networks. CoRR abs/1712.06302 (2017) - 2016
- [j3]José Oramas M., Tinne Tuytelaars:
Recovering hard-to-find object instances by sampling context-based object proposals. Comput. Vis. Image Underst. 152: 118-130 (2016) - [i4]José Oramas M., Tinne Tuytelaars:
Modeling Visual Compatibility through Hierarchical Mid-level Elements. CoRR abs/1604.00036 (2016) - [i3]Marc Martínez-Camarena, José Oramas M., Mario Montagud Climent, Tinne Tuytelaars:
Reasoning about Body-Parts Relations for Sign Language Recognition. CoRR abs/1607.06356 (2016) - 2015
- [b1]José Oramas Mogrovejo:
Context-based Reasoning for Object Detection and Object Pose Estimation ; Gebruik van context voor voorwerpherkenning en pose estimatie. Katholieke Universiteit Leuven, Belgium, 2015 - [c8]Basura Fernando, Efstratios Gavves, José Oramas M., Amir Ghodrati, Tinne Tuytelaars:
Modeling video evolution for action recognition. CVPR 2015: 5378-5387 - [c7]Marc Martínez-Camarena, José Oramas M., Tinne Tuytelaars:
Towards sign language recognition based on body parts relations. ICIP 2015: 2454-2458 - [i2]José Oramas M., Tinne Tuytelaars:
Recovering hard-to-find object instances by sampling context-based object proposals. CoRR abs/1511.01954 (2015) - [i1]Basura Fernando, Efstratios Gavves, José Oramas M., Amir Ghodrati, Tinne Tuytelaars:
Rank Pooling for Action Recognition. CoRR abs/1512.01848 (2015) - 2014
- [j2]Laura Antanas, Martijn van Otterlo, José Oramas Mogrovejo, Tinne Tuytelaars, Luc De Raedt:
There are plenty of places like home: Using relational representations in hierarchies for distance-based image understanding. Neurocomputing 123: 75-85 (2014) - [c6]José Oramas M., Tinne Tuytelaars:
Scene-driven Cues for Viewpoint Classification for Elongated Object Classes. BMVC 2014 - [c5]José Oramas M., Luc De Raedt, Tinne Tuytelaars:
Towards cautious collective inference for object verification. WACV 2014: 269-276 - 2013
- [c4]José Oramas M., Luc De Raedt, Tinne Tuytelaars:
Allocentric Pose Estimation. ICCV 2013: 289-296 - [c3]Lieven Billiet, José Oramas M., McElory Hoffmann, Wannes Meert, Laura Antanas:
Rule-based Hand Posture Recognition using Qualitative Finger Configurations Acquired with the Kinect. ICPRAM 2013: 539-542 - 2012
- [c2]Laura Antanas, Martijn van Otterlo, José Oramas M., Tinne Tuytelaars, Luc De Raedt:
A Relational Distance-based Framework for Hierarchical Image Understanding. ICPRAM (2) 2012: 206-218 - 2011
- [j1]José Oramas Mogrovejo, Alejandro Manuel Moreno Celleri, Katherine Chiluiza García:
Potential benets in the learning process of Ecuadorian Sign Language using a Sign Recognition System. e Minds Int. J. Hum. Comput. Interact. 2(7) (2011) - 2010
- [c1]Laura Antanas, Martijn van Otterlo, José Oramas M., Tinne Tuytelaars, Luc De Raedt:
Not Far Away from Home: A Relational Distance-Based Approach to Understanding Images of Houses. ILP 2010: 22-29
Coauthor Index
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last updated on 2024-11-06 20:29 CET by the dblp team
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