The encoding of local features is an essential part for writer identification and writer retrieval.
While CNN activations have already been used as local features in related works, the …

This paper proposes a new system for offline writer identification and writer verification. The
proposed method uses GMM supervectors to encode the feature distribution of individual …

This paper presents an end-to-end neural network system to identify writers through
handwritten word images, which jointly integrates global-context information and a …

Deep Convolutional Neural Networks (CNN) have shown great success in supervised
classification tasks such as character classification or dating. Deep learning methods …

Text-independent writer identification is challenging due to the huge variation of written
contents and the ambiguous written styles of different writers. This paper proposes …

Convolutional neural networks (CNNs) have recently become the state-of-the-art tool for
large-scale image classification. In this work we propose the use of activation features from …

Handwriting-based identification is a fundamental pattern recognition problem that has
attracted considerable interest in recent years. Writer identification is a major challenge …

This paper presents a method for writer retrieval and identification using a feature descriptor
learned by a Convolutional Neural Network. Instead of using a network for classification, we …

Writer identification based on a small amount of text is a challenging problem. In this paper,
we propose a new benchmark study for writer identification based on word or text block …

This paper proposes a novel method for offline text-independent writer identification by
using convolutional neural network (CNN) and joint Bayesian, which consists of two stages …