Search Results for author:
Found 12 papers, 2 papers with code
Noise-Aware Training of Layout-Aware Language Models
Pre-training an extractor model on unlabeled instances of the target document type, followed by a fine-tuning step on human-labeled instances does not work in these scenarios, as it surpasses the maximum allowable training time allocated for the extractor.
Cross-Modal Entity Matching for Visually Rich Documents
This makes it difficult to contextualize the information retrieved from querying these documents and gather actionable insights from them.
Label-Efficient Self-Training for Attribute Extraction from Semi-Structured Web Documents
Prior works rely on a few human-labeled web pages from each target website or thousands of human-labeled web pages from some seed websites to train a transferable extraction model that generalizes on unseen target websites.
Two-phase Dynamic Routing for Micro and Macro-level Equivariance in Multi-Column Capsule Networks
To address this, we propose a novel two-phase dynamic routing protocol that computes agreements between neurons at various layers for micro and macro-level features, following a hierarchical learning paradigm.
A Skip-connected Multi-column Network for Isolated Handwritten Bangla Character and Digit recognition
Finding local invariant patterns in handwrit-ten characters and/or digits for optical character recognition is a difficult task.
Optical Character Recognition
Optical Character Recognition (OCR)
Interpretable Multi-Headed Attention for Abstractive Summarization at Controllable Lengths
Abstractive summarization at controllable lengths is a challenging task in natural language processing.
A Genetic Algorithm based Kernel-size Selection Approach for a Multi-column Convolutional Neural Network
Deep neural network-based architectures give promising results in various domains including pattern recognition.
Using dynamic routing to extract intermediate features for developing scalable capsule networks
Capsule networks have gained a lot of popularity in short time due to its unique approach to model equivariant class specific properties as capsules from images.
Handwritten Indic Character Recognition using Capsule Networks
Convolutional neural networks(CNNs) has become one of the primary algorithms for various computer vision tasks.
A K-Competitive Autoencoder for Aggression Detection in Social Media Text
Using the encoding generated by Emoti-KATE, a 3-way classification is performed for every social media text in the dataset.
Combining Multi-level Contexts of Superpixel using Convolutional Neural Networks to perform Natural Scene Labeling
Modern deep learning algorithms have triggered various image segmentation approaches.
An Enhanced Harmony Search Method for Bangla Handwritten Character Recognition Using Region Sampling
A new region selection technique based on the idea of an enhanced Harmony Search methodology has been proposed here.
