this project is influence by Learning Features for Offline Handwritten Signature Verification with CNN paper.
in the paper they proposed a multi-task feature extractor.
we did Implementation in 3 different way:
- Training Separated CNN as feature extractor, and then using SVMs for classification.
- Training shared CNN as feature extractor, and then using SVMs for classification.
- Training shared CNN as feature extractor, and then using RNNs (LSTM, GRU, ...) for classification.
the documentation and presentation for each part is included.
requirements to run:
- tensorflow 1.x
- keras
- opencv