Face Aging Caae
Age Progression/Regression by Conditional Adversarial Autoencoder
| Project Name | Stars | Downloads | Repos Using This | Packages Using This | Most Recent Commit | Total Releases | Latest Release | Open Issues | License | Language |
|---|---|---|---|---|---|---|---|---|---|---|
| Face Aging Caae | 497 | 5 years ago | 33 | Python | ||||||
| Age Progression/Regression by Conditional Adversarial Autoencoder | ||||||||||
| Network_anomaly_detection_deep_learning | 9 | 5 years ago | 8 | mit | Jupyter Notebook | |||||
| This project has been conducted under the supervision of Dr. Jinoh Kim and Dr. Donghwoon Kwon at Texas A&M University-Commerce. The research outcome are published in the proceeding of IEEE ICNC 2018 (http://www.conf-icnc.org/2018/), with the title of “An Empirical Evaluation of Deep Learning for Network Anomaly Detection”. | ||||||||||
| Zchainer | 5 | 8 years ago | 10 | April 16, 2016 | Python | |||||
| scikit-learn like interface and stacked autoencoder for chainer | ||||||||||
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