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On the Impact of Interpretability Methods in Active Image Augmentation Method
Robustness is a significant constraint in machine learning models. The p...
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Training Aware Sigmoidal Optimizer
Proper optimization of deep neural networks is an open research question...
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DQN-AF: Deep Q-Network based Adaptive Forwarding Strategy for Named Data Networking
NDN has gained significant attention due to the appearance of several un...
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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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Morphological Skip-Gram: Using morphological knowledge to improve word representation
Natural language processing models have attracted much interest in the d...
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Distantly-Supervised Neural Relation Extraction with Side Information using BERT
Relation extraction (RE) consists in categorizing the relationship betwe...
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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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AM-MobileNet1D: A Portable Model for Speaker Recognition
Speaker Recognition and Speaker Identification are challenging tasks wit...
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Squeezed Deep 6DoF Object Detection Using Knowledge Distillation
The detection of objects considering a 6DoF pose is common requisite to ...
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Improving Deep Image Clustering With Spatial Transformer Layers
Image clustering is an important but challenging task in machine learnin...
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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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Heartbeat Anomaly Detection using Adversarial Oversampling
Cardiovascular diseases are one of the most common causes of death in th...
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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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Additive Margin SincNet for Speaker Recognition
Speaker Recognition is a challenging task with essential applications su...
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Hierarchical Attentional Hybrid Neural Networks for Document Classification
Document classification is a challenging task with important application...
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