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2. Continuous Sign Language Recognition Using Deep Learning Models

open_access
Open Access
Author:
Rahman, Rayhan
Title:
Continuous Sign Language Recognition Using Deep Learning Models
Area of Honors:
Computer Engineering
Keywords:
deep learning
DGS
sign language
continuous sign language recognition
LSTM
Encoder
Encoder-Decoder
RNN
CNN
WER
RWTH-PHOENIX
HMM
CTC Loss
Cross-Entropy Loss
Softmax Function
Loss Function
File:
Download Rahman_Thesis.pdf
Thesis Supervisors:
Mahanth Gowda, Thesis Supervisor
John Morgan Sampson, Thesis Honors Advisor

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