Writer identification for historical handwritten documents using a single feature extraction method
With the growth of artificial intelligence techniques the problem of writer identification from
historical documents has gained increased interest. It consists on knowing the identity of …
historical documents has gained increased interest. It consists on knowing the identity of …
Offline writer identification using convolutional neural network and vlad descriptors
D Liang, M Wu, Y Hu - Artificial Intelligence and Security: 7th International …, 2021 - Springer
This paper proposes a method for writer identification and retrieval. The focus of these two
tasks is to extract discriminative features from handwriting documents. Traditional artificial …
tasks is to extract discriminative features from handwriting documents. Traditional artificial …
A deep learning framework for text-independent writer identification
Abstract Handwriting Writer Identification (HWI) refers to the process of handwriting text
image analysis to identify the authorship of the documents. It has yielded promising results …
image analysis to identify the authorship of the documents. It has yielded promising results …
Deep neural networks-based offline writer identification using heterogeneous handwriting data: an evaluation via a novel standard dataset
In modern societies, handwritten identification is a great practical need and challenge for
forensic sciences. Moreover, few research studies have focused on automatic offline …
forensic sciences. Moreover, few research studies have focused on automatic offline …
Unsupervised feature learning for writer identification and writer retrieval
V Christlein, M Gropp, S Fiel… - 2017 14th IAPR …, 2017 - ieeexplore.ieee.org
Deep Convolutional Neural Networks (CNN) have shown great success in supervised
classification tasks such as character classification or dating. Deep learning methods …
classification tasks such as character classification or dating. Deep learning methods …
A comparative study of machine learning approaches for handwriter identification
A Durou, S Al-Maadeed, I Aref… - 2019 IEEE 12th …, 2019 - ieeexplore.ieee.org
During the past few years, writer identification has attracted significant interest due to its real-
life applications including document analysis, forensics etc. Machine learning algorithms …
life applications including document analysis, forensics etc. Machine learning algorithms …
Dual-pathway deep CNN for offline writer identification
Writer Identification is a challenging problem based on small amount of handwritten text. It is
also a foremost research topic in forensic analysis of documents. For this, a convolution …
also a foremost research topic in forensic analysis of documents. For this, a convolution …
Length independent writer identification based on the fusion of deep and hand-crafted descriptors
Writer's identification from a handwritten text is one of the most challenging machines
learning problems because of the variable handwritten sources, various languages, the …
learning problems because of the variable handwritten sources, various languages, the …
Writer characterization from handwriting on papyri using multi-step feature learning
Identification of scribes from historical manuscripts has remained an equally interesting
problem for paleographers as well as the pattern classification researchers. Though …
problem for paleographers as well as the pattern classification researchers. Though …
Segmentation-free writer identification based on convolutional neural network
P Kumar, A Sharma - Computers & Electrical Engineering, 2020 - Elsevier
Handwriting recognition is one of the desired aspects of document understanding and
analysis. It deals with the writing style of the document and learns the features which …
analysis. It deals with the writing style of the document and learns the features which …