… Global information is encoded using topological information of … In this system, a CNN,
pre-trained for writer identification task … hybrid model (CNN-BiLSTM) with ReLU activation is better …

… Automatic handwriting recognition systems can have a range of uses: recognition of hand-written …
have decreased the coding length, but at the expense of increased code complexity. …

… of writing of different peoples as it is not an Optical character … CNN employs different activation
functions at each layer to … Next, we performed one-hot encoding to convert the y values …

… fed to RNN–LSTM for encoding the visual features and decoding … This paper focuses on
offline handwriting recognition … layer have full connections to all activations in the previous layer, …

… The encoder part is used to transform the input data into a low … The activation function used
in all the layers is ReLU, which … of characters and inconsistency in writing style. The fact that …

… the handwriting recognition field for designing CNN parameters … ReLU is one of the most
widely used activation functions in … A system for offline character recognition using auto-encoder …

… By style of writing we mean the orientation of his/her palm, … Our results suggests that this
enables the Autoencoder to encode … the result through an Activation function such as sigmoid …

… Handwriting recognition, depending upon the type of data as … pooling to calculate class
activation maps for offline Chinese … ] used deep encoder and CNN for recognition of handwritten …

… and the isolated Arabic character recognition, the latter is … writing styles. This paper proposes
a multi-stage cascading system to serve the field of offline Arabic handwriting recognition. …

… patches and the deep learned features are encoded using the vector of locally aggregated …
learned deep features are encoded using VLAD for offline writer identification based on word-…