This paper presents a Convolutional Neural Network (CNN) for document image
classification. In particular, document image classes are defined by the structural similarity …

We propose an effective method for automatic writer recognition from unconstrained
handwritten text images. Our method relies on two different aspects of writing: the presence …

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 …

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 …

This paper presents a novel approach to defining document image structural similarity for
the applications of classification and retrieval. We first build a codebook of SURF descriptors …

This paper presents a system to predict gender of individuals from offline handwriting
samples. The technique relies on extracting a set of textural features from handwriting …

This paper presents a novel two-stream approach for document image classification. The
proposed approach leverages textual and visual modalities to classify document images into …

There have been much interest and a large amount of research on content based image
retrieval (CBIR) in recent years due to the ever increasing number of digital images. Texture …

In this paper, we present a learning based approach for computing structural similarities
among document images for unsupervised exploration in large document collections. The …

This paper presents an efficient anticollision algorithm for the RFID tags communication
conflict. The novelty of our algorithm is that we map a set of n tags into a corresponding …