… writer identification method by employing CNN in this work. In this section, the details of
feature extraction based on CNN … extracted features are directly used for writer identification in …

… In this paper, we propose a simple, yet effective, way to learn CNN activation features in an
… CNN layer serve as features for subsequent classification tasks. We evaluate the feature …

… In this section, we will elaborate the related work in the field of automated writer identification
… We also explore the fusion of different architectures of CNN. We also aim to evaluate the …

… In addition, we find that different languages such as English and Chinese may share
common features for writer identification, and joint training can yield better performance. …

… To alleviate these problems, we introduce a path-signature feature to writer identification
because of its ability to uniquely characterize the trajectory of a character. The extracted feature …

… Therefore, we propose to use an end-to-end network for writer identification, where the
CNN-based feature extractor and the neural network-based classifier are connected and trained …

… uses CNN for the task of writer identification and writer retrieval. Since a feature vector is …
a comparison with precalculated features in a dataset to identify a specific writer or to search for …

… features like SIFT, HOG, SURF and CNN based features etc. was not discussed. In 2012,
Awaida [20] presented the state of art of writer identification … research groups, feature extraction …

… features, then they aggregated the results in a global feature … writers without requirement of
prior identification of features [9… in conjunction with CNN as feature extraction method would …

… Some of the methods utilized the CNN based features for writer identification but required …
In this research, the power of deep CNN is utilized for writer identification of handwritten text …