ITM Web Conf.
Volume 40, 2021International Conference on Automation, Computing and Communication 2021 (ICACC-2021)
|Number of page(s)||6|
|Published online||09 August 2021|
- S. Chandran, Pournami Balakrishnan, Byju Rajasekharan, Deepak N Nishakumari, K Devanand, P M Sasi, P. (2018). “Missing Child Identification System Using Deep Learning and Multiclass SVM ”. [Google Scholar]
- 2. Xin Jin, Shiming Ge, Chenggen Song, Xiaodong Li, Jicheng Lei, Chuanqiang Wu, and Haoyang Yu “Double-Blinded Finder: A Two-SidePrivacy-Preserving Approach for Finding Missing Children”(2020). [Google Scholar]
- Shun Lei Myat Oo, Aung Nway Oo University of Information Technology, Yangon, Myanmar “ Child Face Recognition with Deep Learning”(2019). [Google Scholar]
- Chang Shu School of Communication and Information Engineering, University of Electronic Science and Technology of China Chengdu, China “Optimizing deep neural network structure for face recognition” (2017). [Google Scholar]
- Grigory Antipov, Moez Baccouche, Jean-Luc Dugelay ”Face Aging with Conditional Generative Adversarial Networks” (2017) arXiv:1702.01983v2. [Google Scholar]
- Florian Schroff, Dmitry Kalenichenko, and James Philbin. Facenet: A unified embedding for face recognition and clustering. In CVPR, pages 815–823, 2015. [Google Scholar]
- Hao Wang, Yitong Wang, Zheng Zhou, Xing Ji, Dihong Gong, Jingchao Zhou, Zhifeng Li, and Wei Liu. Cosface: Large margin cosine loss for deep face recognition. In CVPR, 2018 [Google Scholar]
- Karl Ricanek Jr., Ph.D. Senior Member IEEE, Shivani Bhardwaj, Michael Sodomsky A Review of Face Recognition against Longitudinal Child Faces [Google Scholar]
- FACE AGING WITH CONDITIONAL GENERATIVE ADVERSARIAL NETWORKS GrigoryAntipov, MoezBaccouche, Jean-Luc Dugelay [Google Scholar]
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.