End to End Recognition System for Recognizing Offline Unconstrained Vietnamese Handwriting

14 May 2019 Anh Duc Le Hung Tuan Nguyen Masaki Nakagawa

Inspired by recent successes in neural machine translation and image caption generation, we present an attention based encoder decoder model (AED) to recognize Vietnamese Handwritten Text. The model composes of two parts: a DenseNet for extracting invariant features, and a Long Short-Term Memory network (LSTM) with an attention model incorporated for generating output text (LSTM decoder), which are connected from the CNN part to the attention model... (read more)

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Methods used in the Paper


METHOD TYPE
Sigmoid Activation
Activation Functions
Tanh Activation
Activation Functions
ReLU
Activation Functions
Batch Normalization
Normalization
Convolution
Convolutions
Average Pooling
Pooling Operations
Concatenated Skip Connection
Skip Connections
Global Average Pooling
Pooling Operations
Dense Block
Image Model Blocks
Kaiming Initialization
Initialization
1x1 Convolution
Convolutions
Dropout
Regularization
Dense Connections
Feedforward Networks
Max Pooling
Pooling Operations
Softmax
Output Functions
DenseNet
Convolutional Neural Networks
Memory Network
Working Memory Models
LSTM
Recurrent Neural Networks