block98k's repositories
Denoise-VAE
Practice denoised VAE used tensorflow
TAIL_CAMP_week_1
视频动作识别
U-Net-keras
U-Net, keras
awesome-object-detection
Awesome Object Detection based on handong1587 github: https://handong1587.github.io/deep_learning/2015/10/09/object-detection.html
awesome_deep_learning_interpretability
深度学习近年来关于神经网络模型解释性的相关高引用/顶会论文(附带代码)
basic-yolo-keras
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).
caffe2
Caffe2 is a lightweight, modular, and scalable deep learning framework.
CuoNet
Cascaded U-O Net (CVPR 2019 Submission)
deblur-gan
Keras implementation of "DeblurGAN: Blind Motion Deblurring Using Conditional Adversarial Networks"
generative-adversarial-networks
Introduction to generative adversarial networks, with code to accompany the O'Reilly tutorial on GANs
GenFlowers-AE
Use traditional autoencoder to generate flowers.
hello-world
my first github repository
keras-ae
用ae降噪,并测试模型的泛化能力
Keras-GAN
Keras implementations of Generative Adversarial Networks.
keras-yolo3
Training and Detecting Objects with YOLO3
Mask_RCNN
Mask R-CNN for object detection and instance segmentation on Keras and TensorFlow
models
Models and examples built with TensorFlow
MyKerasModel
My own keras model libs, Continually updated
neural-backed-decision-trees
Making decision trees competitive with neural networks on CIFAR10, CIFAR100, TinyImagenet200, Imagenet
SVD
参考Daniel Pyrathon的演讲与PyConUs2018,训练SVD的demo
TAIL_CAMP_week_2
TAIL CAMP 第二周作业
TensorBox
Object detection in TensorFlow
TensorFlow-Examples
TensorFlow Tutorial and Examples for Beginners with Latest APIs
tensornets
High level network definitions with pre-trained weights in TensorFlow
tflearn
Deep learning library featuring a higher-level API for TensorFlow.
tvm
Open deep learning compiler stack for cpu, gpu and specialized accelerators
UGATIT
Official Tensorflow implementation of U-GAT-IT: Unsupervised Generative Attentional Networks with Adaptive Layer-Instance Normalization for Image-to-Image Translation