Poisson.G's repositories
deep-transfer-learning
A collection of implementations of deep domain adaptation algorithms
Adversarial-Examples-in-PyTorch
Pytorch code to generate adversarial examples on mnist and ImageNet data.
cs420
final project
doudizhu-rl
强化学习训练斗地主 / doudizhu AI using reinforcement learning.
facenet-pytorch
Pretrained Pytorch face detection (MTCNN) and recognition (InceptionResnet) models
FastPhotoStyle
Style transfer, deep learning, feature transform
final_project
final project
guobaisong
Config files for my GitHub profile.
ICDAR2019_cTDaR
The ICDAR 2019 cTDaR is to evaluate the performance of methods for table detection (TRACK A) and table recognition (TRACK B). For the first track, document images containing one or several tables are provided. For TRACK B two subtracks exist: the first subtrack (B.1) provides the table region. Thus, only the table structure recognition must be performed. The second subtrack (B.2) provides no a-priori information. This means, the table region and table structure detection has to be done.
progressive_growing_of_gans_tensorflow
Tensorflow implementation of PROGRESSIVE GROWING OF GANS FOR IMPROVED QUALITY, STABILITY, AND VARIATION
Reinforcement-learning-with-tensorflow
Simple Reinforcement learning tutorials
vm
:computer: The Nextcloud VM (virtual machine)