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JOINT FACIAL FEATURE EXTRACTION AND FACIAL IMAGE QUALITY ESTIMATION USING A DEEP NEURAL NETWORK (DNN) TRAINED WITH A CUSTOM-LABELED TRAINING DATASET AND HAVING A COMMON DNN BACKBONE
JOINT FACIAL FEATURE EXTRACTION AND FACIAL IMAGE QUALITY ESTIMATION USING A DEEP NEURAL NETWORK (DNN) TRAINED WITH A CUSTOM-LABELED TRAINING DATASET AND HAVING A COMMON DNN BACKBONE
Systems and methods for joint feature extraction and quality prediction using a shared machine learning model backbone and a customized training dataset are provided. According to an embodiment, a computer system receives a training dataset including example images each labeled with a particular category of a set of categories, and trains a deep neural network (DNN) based on the training dataset to jointly perform for an input image (i) facial feature extraction in accordance with the facial feature extraction algorithm and (ii) a quality scoring in accordance with a quality prediction algorithm. In the embodiment, the DNN, once trained with the training dataset labeled using a custom labeling scheme is used for the facial feature extraction and the quality prediction. The facial feature extraction algorithm and the quality prediction algorithm share a common DNN backbone of the DNN.
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