kjunhwa

kjunhwa's Stars

• experiencor/keras-yolo2

  Easy training on custom dataset. Various backends (MobileNet and SqueezeNet) supported. A YOLO demo to detect raccoon run entirely in brower is accessible at https://git.io/vF7vI (not on Windows).

  Language:Jupyter Notebook1.7k784

• kozistr/Awesome-GANs

  Awesome Generative Adversarial Networks with tensorflow

  Language:Python760163

• kesamet/dcgan_tensorflow

  First experiments with DCGAN

  Language:Jupyter Notebook1

• Overseer66/Tensorflow-GAN

  GAN / DCGAN / InfoGAN / BEGAN ...

  Language:Jupyter Notebook67

• zzsza/Deep_Learning_starting_with_the_latest_papers

  최신 논문으로 시작하는 딥러닝 강의 (개정된 강의 이름 : 논문으로 짚어보는 딥러닝의 맥) 기록

  Language:Jupyter Notebook8218

• jfzhang95/pytorch-video-recognition

  PyTorch implemented C3D, R3D, R2Plus1D models for video activity recognition.

  Language:Python1.2k252

• hunkim/PyTorchZeroToAll

  Simple PyTorch Tutorials Zero to ALL!

  Language:Python3.9k1.2k

• gilbutITbook/006975

  케라스 창시자에게 배우는 딥러닝

  185245

• Subhanandh/Visual_analysis

  Visual analysis of DenseNet model using Keras

  Language:Jupyter Notebook11

• Oh-Yoojin/DenseNet-keras

  Language:Python1

• RubensZimbres/Repo-2018

  Deep Learning Summer School + Tensorflow + OpenCV cascade training + YOLO + COCO + CycleGAN + AWS EC2 Setup + AWS IoT Project + AWS SageMaker + AWS API Gateway + Raspberry Pi3 Ubuntu Core

  Language:Jupyter Notebook17280

• mafda/generative_adversarial_networks_101

  Keras implementations of Generative Adversarial Networks. GANs, DCGAN, CGAN, CCGAN, WGAN and LSGAN models with MNIST and CIFAR-10 datasets.

  Language:Jupyter Notebook20279