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Research on Face Attribute Recognition Technology Based on Fine-Grained Features

   | 26 lut 2024

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Li, J. B., & Pan, J. S. (2017). Multiple sensors-based kernel machine learning in smart environment. Review of Scientific Instruments, 88(1), 015006. Search in Google Scholar

Lu, B. (2021). A theory of ‘authorship transfer’ and its application to the context of artificial intelligence creations. Queen Mary Journal of Intellectual Property, 11(1), 2-24. Search in Google Scholar

Hutchinson, P. (2020). Reinventing innovation management: the impact of self-innovating artificial intelligence. IEEE Transactions on Engineering Management, PP(99), 1-12. Search in Google Scholar

Ramadoss, J., Venkatesh, J., Joshi, S., Shukla, P. K., Jamal, S. S., & Altuwairiqi, M., et al. (2021). Computer vision for human-computer interaction using noninvasive technology. Sci. Program., 2021, 3902030:1-3902030:15. Search in Google Scholar

Berezowski, T. L. E. (2021). Evaluating the morphological and metric sex of human crania using 3-dimensional (3d) technology. International journal of legal medicine, 135(3). Search in Google Scholar

Nan, Z., Yi, C., Maolong, X., Fangqin, W., & Yanwen, Q. (2018). Feature extraction based on low-rank affinity matrix for biological recognition. Journal of Computational ence, 27, 199-205. Search in Google Scholar

Martins, J. A., Lam, R. L., Rodrigues, J. M. F., & Du Buf, J. M. H. (2018). Expression-invariant face recognition using a biological disparity energy model. Neurocomputing, 297(JUL.5), 82-93. Search in Google Scholar

Meden, B., Mall, R. C., Fabijan, S., Ekenel, H. K., Truc, V., & Peer, P. (2017). Face deidentification with generative deep neural networks. Iet Signal Processing, 11(9), 1046-1054. Search in Google Scholar

Grm, K., ?truc, Vitomir, Artiges, A., Caron, M., & Ekenel, H. K. (2018). Strengths and weaknesses of deep learning models for face recognition against image degradations. Iet Biometrics, 7(1), 81-89. Search in Google Scholar

Hassan, Akhavein, Reza, & Farivar. (2017). Gaze behavior during 3-d face identification is depth cue invariant. Journal of Vision. Search in Google Scholar

Roux-Sibilon, A., Peyrin, C., Greenwood, J. A., & Valérie Goffaux. (2021). Radial biases influence face identification in the periphery. Journal of Vision, 21(9), 2594-. Search in Google Scholar

Liu, D. (2022). 3d face geometry optimization using artificial intelligence and computer graphics. Scientific Programming. Search in Google Scholar

Colon, Y. I., Castillo, C. D., & Otoole, A. (2021). Facial expression is retained in deep networks trained for face identification. Journal of Vision. Search in Google Scholar

Cheng, Z., Zhu, X., & Gong, S. (2020). Face re-identification challenge: are face recognition models good enough?. Pattern Recognition, 107(5), 107422. Search in Google Scholar

Medapati, P. K., Murthy, P. H. S. T., & Sridhar, K. P. (2019). Lamstar: for iot‐based face recognition system to manage the safety factor in smart cities. Transactions on Emerging Telecommunications Technologies. Search in Google Scholar

Wang, P. B. X. (2018). Regional parallel structure based cnn for thermal infrared face identification. Integrated Computer-Aided Engineering, 25(3). Search in Google Scholar

Wang, R., Shi, Z. F., Li, Q., Gao, R., Zhao, C., & Feng, L. (2021). Pig face recognition model based on a cascaded network. Applied Engineering in Agriculture(5), 37. Search in Google Scholar

Choi, J. Y. (2017). Improved deep face identification with multi-class pairwise discriminant loss. Electronics Letters, 53(20), 1356-1358. Search in Google Scholar

eISSN:
2444-8656
Język:
Angielski
Częstotliwość wydawania:
Volume Open
Dziedziny czasopisma:
Life Sciences, other, Mathematics, Applied Mathematics, General Mathematics, Physics