Using Convolutional Neural Networks to Discover Cogntively Validated Features for Gender Classification

• Published in: 2014 International Conference on Soft Computing and Machine Intelligence pp. 33 - 37
• Main Authors: Verma, Ankit, Vig, Lovekesh
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01.09.2014
• Subjects: Accuracy; backpropagation algorithm; Biological neural networks; Convolution; convolutional neural network; Face recognition; Feature extraction; gender classification; horizontal flipping; L2 Regularization; Robustness; Training

The human visual cortex is extremely adept at distinguishing between male and female faces, or performing "Gender Classification". While the subject of face detection and recognition has received a lot of focus, research into the features or cognitive processes that are useful for identify...