kxlwolf's starred repositories
awesome-semantic-segmentation
:metal: awesome-semantic-segmentation
deep_sort_pytorch
MOT using deepsort and yolov3 with pytorch
knowledge-distillation-pytorch
A PyTorch implementation for exploring deep and shallow knowledge distillation (KD) experiments with flexibility
awesome-knowledge-distillation
Awesome Knowledge Distillation
MachineLearning
Machine learning resources,including algorithm, paper, dataset, example and so on.
Kalman-and-Bayesian-Filters-in-Python
Kalman Filter book using Jupyter Notebook. Focuses on building intuition and experience, not formal proofs. Includes Kalman filters,extended Kalman filters, unscented Kalman filters, particle filters, and more. All exercises include solutions.
deep_sort_yolov3
Real-time Multi-person tracker using YOLO v3 and deep_sort with tensorflow
Awesome-Crowd-Counting
Awesome Crowd Counting
C-3-Framework
An open-source PyTorch code for crowd counting
CornerNet-Lite-Pytorch
:rotating_light::rotating_light::rotating_light: CornerNet:基于虚拟仿真环境下的自动驾驶交通标志识别
keras-applications
Reference implementations of popular deep learning models.
cnn_finetune
Fine-tune CNN in Keras
keras-retinanet
Keras implementation of RetinaNet object detection.
deep_learning_object_detection
A paper list of object detection using deep learning.
darknet-mobilenet
mobilenet model in darknet framework , MobilenetYOLO, compress mobilenet
awesome-object-detection
Awesome Object Detection based on handong1587 github: https://handong1587.github.io/deep_learning/2015/10/09/object-detection.html
tensorflow-docs
TensorFlow 最新官方文档中文版
pytorch-handbook
pytorch handbook是一本开源的书籍,目标是帮助那些希望和使用PyTorch进行深度学习开发和研究的朋友快速入门,其中包含的Pytorch教程全部通过测试保证可以成功运行
Tensorflow-TensorRT
This repository is for my YT video series about optimizing a Tensorflow deep learning model using TensorRT. We demonstrate optimizing LeNet-like model and YOLOv3 model, and get 3.7x and 1.5x faster for the former and the latter, respectively, compared to the original models.
pytorch-cifar
95.47% on CIFAR10 with PyTorch