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08/06/2022
Towards Robust Deep Learning using Entropic Losses
Current deep learning solutions are well known for not informing whether...
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05/12/2022
Distinction Maximization Loss: Efficiently Improving Classification Accuracy, Uncertainty Estimation, and Out-of-Distribution Detection Simply Replacing the Loss and Calibratin
Building robust deterministic neural networks remains a challenge. On th...
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11/03/2021
Multi-Cue Adaptive Emotion Recognition Network
Expressing and identifying emotions through facial and physical expressi...
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05/30/2021
Improving Entropic Out-of-Distribution Detection using Isometric Distances and the Minimum Distance Score
Current out-of-distribution detection approaches usually present special...
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02/17/2021
Training Aware Sigmoidal Optimizer
Proper optimization of deep neural networks is an open research question...
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08/16/2020
KutralNet: A Portable Deep Learning Model for Fire Recognition
Most of the automatic fire alarm systems detect the fire presence throug...
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06/07/2020
Neural Networks Out-of-Distribution Detection: Hyperparameter-Free Isotropic Maximization Loss, The Principle of Maximum Entropy, Cold Training, and Branched Inferences
Current out-of-distribution detection (ODD) approaches present severe dr...
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04/29/2020
Distantly-Supervised Neural Relation Extraction with Side Information using BERT
Relation extraction (RE) consists in categorizing the relationship betwe...
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04/03/2020
A Fast Fully Octave Convolutional Neural Network for Document Image Segmentation
The Know Your Customer (KYC) and Anti Money Laundering (AML) are worldwi...
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03/31/2020
AM-MobileNet1D: A Portable Model for Speaker Recognition
Speaker Recognition and Speaker Identification are challenging tasks wit...
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03/30/2020
Squeezed Deep 6DoF Object Detection Using Knowledge Distillation
The detection of objects considering a 6DoF pose is common requisite to ...
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08/15/2019
Distinction Maximization Loss: Fast, Scalable, Turnkey, and Native Neural Networks Out-of-Distribution Detection simply by Replacing the SoftMax Loss
Recently, many methods to reduce neural networks uncertainty have been p...
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01/31/2019
Spatial-Temporal Graph Convolutional Networks for Sign Language Recognition
The recognition of sign language is a challenging task with an important...
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01/28/2019
Heartbeat Anomaly Detection using Adversarial Oversampling
Cardiovascular diseases are one of the most common causes of death in th...
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01/28/2019
Squeezed Very Deep Convolutional Neural Networks for Text Classification
Most of the research in convolutional neural networks has focused on inc...
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01/28/2019
Additive Margin SincNet for Speaker Recognition
Speaker Recognition is a challenging task with essential applications su...
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01/20/2019