Perception of Age and Gender Detection by using Hierarchical Deep Learning Architecture through Vision
M. Praveena, K. Geetha Srinija, Alokam Meghana · 2022 International Conference on Sustainable Computing and Data Communication Systems (ICSCDS) · 2022
When it comes to software systems that analyze face photos, gender detection is a crucial feature. This research provides a quantum machine learning-based approach for automated gender categorization from face photos utilizing a hybrid classical-quantum neural network, which is based on quantum machine learning. Using the knowledge of a pre-trained off-the-shelf Deep Neural Network (DNN)in conjunction with the transfer learning of a quantum variational circuit, an accurate binary classifier has been produced in this paper. An example of a hybrid network is the binary classifier, which is composed of a convolutional base of the Deep Neural Network (DNN) that has been compressed with a dressed quantum circuit and a dressed quantum circuit. In the classification of a publicly accessible collection of face photographs, better results than that have been previously reported have been obtained.