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05/23/2020
Self-supervised Robust Object Detectors from Partially Labelled datasets
In the object detection task, merging various datasets from similar cont...
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05/17/2020
Toward Adversarial Robustness by Diversity in an Ensemble of Specialized Deep Neural Networks
We aim at demonstrating the influence of diversity in the ensemble of CN...
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10/18/2019
Toward Metrics for Differentiating Out-of-Distribution Sets
Vanilla CNNs, as uncalibrated classifiers, suffer from classifying out-o...
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03/21/2019
A Principled Approach for Learning Task Similarity in Multitask Learning
Multitask learning aims at solving a set of related tasks simultaneously...
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08/21/2018
Controlling Over-generalization and its Effect on Adversarial Examples Generation and Detection
Convolutional Neural Networks (CNNs) allowed improving the state-of-the-...
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04/24/2018
Towards Dependable Deep Convolutional Neural Networks (CNNs) with Out-distribution Learning
Detection and rejection of adversarial examples in security sensitive an...
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02/20/2018
Out-distribution training confers robustness to deep neural networks
The easiness at which adversarial instances can be generated in deep neu...
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02/22/2017
Robustness to Adversarial Examples through an Ensemble of Specialists
We are proposing to use an ensemble of diverse specialists, where specia...
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11/05/2016