Charting the Right Manifold: Manifold Mixup for Few-shot Learning
Few-shot learning algorithms aim to learn model parameters capable of adapting to unseen classes with the help of only a few labeled …
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Document Structure Extraction using Prior based High Resolution Hierarchical Semantic Segmentation
Structure extraction from document images has been a long-standing research topic due to its high impact on a wide range of practical …
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Explain Your Move: Understanding Agent Actions Using Specific and Relevant Feature Attribution
As deep reinforcement learning (RL) is applied to more tasks, there is a need to visualize and understand the behavior of learned …
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Form2Seq : A Framework for Higher-Order Form Structure Extraction
Document structure extraction has been a widely researched area for decades with recent works performing it as a semantic segmentation …
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Harnessing GANs for Zero-shot Learning of New Classes in Visual Speech Recognition
Visual Speech Recognition (VSR) is the process of recognizing or interpreting speech by watching the lip movements of the speaker. …
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Keyphrase Extraction as Sequence Labeling Task using Transformers
In this paper, we formulate keyphrase extraction from scholarly articles as a sequence labeling task solved using a BiLSTM-CRF, where …
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Learning based Methods for Code Runtime Complexity Prediction
Predicting the runtime complexity of a programming code is an arduous task. In fact, even for humans, it requires a subtle analysis and …
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MixBoost: Synthetic Oversampling with Boosted Mixup for Handling Extreme Imbalance
Training a classification model on a dataset where the instances of one class outnumber those of the other class is a challenging …
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Multi-Modal Association based Grouping for Form Structure Extraction
Document structure extraction has been a widely researched area for decades. Recent work in this direction has been deep …
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Retrospective Loss: Looking Back to Improve Training of Deep Neural Networks
Deep neural networks (DNNs) are powerful learning machines that have enabled breakthroughs in several domains. In this work, we …
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