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José Oramas M.
José Oramas Mogrovejo – José Oramas
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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
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
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 - [i24]Fabian Denoodt, Bart de Boer, José Oramas:
Smooth InfoMax - Towards easier Post-Hoc interpretability. CoRR abs/2408.12936 (2024) - [i23]Hamed Behzadi-Khormouji, José Oramas:
Deep Model Interpretation with Limited Data : A Coreset-based Approach. CoRR abs/2410.00524 (2024) - [i22]Salma Haidar, José Oramas:
Enhancing Hyperspectral Image Prediction with Contrastive Learning in Low-Label Regime. CoRR abs/2410.07790 (2024) - [i21]Michael T. Pearce, Thomas Dooms, Alice Rigg, José Oramas M., Lee Sharkey:
Bilinear MLPs enable weight-based mechanistic interpretability. CoRR abs/2410.08417 (2024) - 2023
- [j6]Salma Haidar
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
Automated Virtual Reduction of Displaced Distal Radius Fractures. ISBI 2023: 1-4 - [c28]Mattias Billast, Kevin Mets, Tom De Schepper
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
AIMLAI: Advances in Interpretable Machine Learning and Artificial Intelligence. CIKM 2022: 5160 - [c24]Mattias Billast, Robin Janssens
Object Detection To Enable Autonomous Vessels On European Inland Waterways. IECON 2022: 1-6 - [c23]Akash Singh
Deep Set Conditioned Latent Representations for Action Recognition. VISIGRAPP (5: VISAPP) 2022: 456-466 - [i14]Akash Singh
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
Task Independent Capsule-Based Agents for Deep Q-Learning. BNAIC/BENELEARN 2021: 69-85 - [c20]Mattias Billast, Tom De Schepper
Object Detection with Semi-supervised Adversarial Domain Adaptation for Real-Time Edge Devices. BNAIC/BENELEARN 2021: 86-102 - [e2]Michael Kamp
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
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.
Multiple Exemplars-Based Hallucination for Face Super-Resolution and Editing. ACCV (5) 2020: 258-273 - [c18]Kaili Wang, José Oramas M.
In Defense of LSTMs for Addressing Multiple Instance Learning Problems. ACCV (6) 2020: 444-460 - [c17]Adrien Bibal
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.
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
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.
From Pixels to Actions: Learning to Drive a Car with Deep Neural Networks. WACV 2018: 606-615 - [c9]Kaili Wang, Yu-Hui Huang
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.
Context-based object viewpoint estimation: A 2D relational approach. Comput. Vis. Image Underst. 160: 100-113 (2017) - [j4]Basura Fernando
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.
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.
Modeling video evolution for action recognition. CVPR 2015: 5378-5387 - [c7]Marc Martínez-Camarena, José Oramas M.
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
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.
Towards cautious collective inference for object verification. WACV 2014: 269-276 - 2013
- [c4]José Oramas M.
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.
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 2024-12-08 02:24 CET by the dblp team
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