Learning to represent 2D human face with mathematical model
Learning to represent 2D human face with mathematical model is a scholarly work, published in 2024 in ''CAAI Transactions on Intelligence Technology''. The main subjects of the publication include political representation, image, convolutional neural network, artificial intelligence, generative adversarial network, computer vision, expression, facial recognition system, encoder, benchmark, pixel, face, pattern recognition, computer science, and Human visual system model. The authors demonstrate that the authors' EmFace represents face image more accurate than the comparison method, with an average mean square error of 0.000888, 0.000936, 0.000953 on LFW, IARPA Janus Benchmark‐B, and IJB‐C datasets.