Kylin's starred repositories
Efficient-AI-Backbones
Efficient AI Backbones including GhostNet, TNT and MLP, developed by Huawei Noah's Ark Lab.
tensorflow-yolov3
🔥 TensorFlow Code for technical report: "YOLOv3: An Incremental Improvement"
EfficientNet-Light-Head-RCNN
Person Detection using the EfficientNet B0 and Light Head RCNN running at 12 FPS
CrossStagePartialNetworks
Cross Stage Partial Networks
keras-yolo3
A Keras implementation of YOLOv3 (Tensorflow backend)
mobilenetv2-yolov3
yolov3 with mobilenetv2 and efficientnet
SSD_EfficientNet
SSD using TensorFlow object detection API with EfficientNet backbone
PINTO_model_zoo
A repository for storing models that have been inter-converted between various frameworks. Supported frameworks are TensorFlow, PyTorch, ONNX, OpenVINO, TFJS, TFTRT, TensorFlowLite (Float32/16/INT8), EdgeTPU, CoreML.
PythonRobotics
Python sample codes for robotics algorithms.
efficientdet
(Pretrained weights provided) EfficientDet: Scalable and Efficient Object Detection implementation by Signatrix GmbH
EfficientDet.Pytorch
Implementation EfficientDet: Scalable and Efficient Object Detection in PyTorch
Thundernet_Pytorch
Implementation Thundernet
awesome-object-detection
Awesome Object Detection based on handong1587 github: https://handong1587.github.io/deep_learning/2015/10/09/object-detection.html
Awesome_DNN_Researchers
We will introduce the researchers who made great contributions to DNNs in the projects.
awesome-deep-learning
A curated list of awesome Deep Learning tutorials, projects and communities.
TensorFlow-Object-Detection-on-the-Raspberry-Pi
A tutorial showing how to set up TensorFlow's Object Detection API on the Raspberry Pi
DeepInterests
深度有趣
deeplearning-models
A collection of various deep learning architectures, models, and tips
DCGAN-tensorflow
A tensorflow implementation of "Deep Convolutional Generative Adversarial Networks"
3D-Machine-Learning
A resource repository for 3D machine learning
DeepLearning-500-questions
深度学习500问,以问答形式对常用的概率知识、线性代数、机器学习、深度学习、计算机视觉等热点问题进行阐述,以帮助自己及有需要的读者。 全书分为18个章节,50余万字。由于水平有限,书中不妥之处恳请广大读者批评指正。 未完待续............ 如有意合作,联系scutjy2015@163.com 版权所有,违权必究 Tan 2018.06