In the last decade, deep learning has reinvigorated the machine learning field. It has solved
many problems in computer vision, speech recognition, natural language processing, and …

Understanding document images (eg, invoices) is a core but challenging task since it
requires complex functions such as reading text and a holistic understanding of the …

This paper presents a new state-of-the-art for document image classification and retrieval,
using features learned by deep convolutional neural networks (CNNs). In object and scene …

Background and objectives The calcaneus is the most fracture-prone tarsal bone and
injuries to the surrounding tissue are some of the most difficult to treat. Currently there is a …

In the last decade or so, we have witnessed deep learning reinvigorating the machine
learning field. It has solved many problems in the domains of computer vision, speech …

Within the realm of information extraction from documents, detection of tables and charts is
particularly needed as they contain a visual summary of the most valuable information …

Automatic segmentation of brain sub regions such as White Matter (GM), Corpus Callosum
(CC), Grey Matter (WM) and Hippocampus (HC) is a challenging task due to the variations in …

This paper presents a deep Convolutional Neural Network (CNN) based approach for
document image classification. One of the main requirement of deep CNN architecture is …

This paper presents an approach for real-time training and testing for document image
classification. In production environments, it is crucial to perform accurate and (time-) …

We present an exhaustive investigation of recent Deep Learning architectures, algorithms,
and strategies for the task of document image classification to finally reduce the error by …