Mr.Paper

@MrPaper

Mr.Paper 暂无简介

所有 个人的 我参与的
Forks 暂停/关闭的

    Mr.Paper/kitti_object_vis

    fork github

    Mr.Paper/Yolo3D

    fork github repo

    Mr.Paper/mmyolo_fork

    fork mmlab

    Mr.Paper/TensorRT

    fork

    Mr.Paper/mmselfsup

    fork mmselfsup

    Mr.Paper/EgoNet

    fork github

    Mr.Paper/mmdetection_3.0x

    fork github

    Mr.Paper/yolov5-rt-stack

    yolort / yet another yolov5, with its runtime stack for libtorch, onnx, tvm, ncnn and specialized accelerators.

    Mr.Paper/mmdetection_fork

    OpenMMLab Detection Toolbox and Benchmark

    Mr.Paper/mmdetection forked from 我爱计算机视觉/mmdetection

    MMDetection是基于PyTorch的开源目标检测工具箱。是OpenMMLab最知名的开源库,几乎是研究目标检测必备! 代码原地址:https://github.com/open-mmlab/mmdetection

    Mr.Paper/Vitis-AI

    Vitis AI is Xilinx’s development stack for AI inference on Xilinx hardware platforms, including both edge devices and Alveo cards.

    Mr.Paper/caffe-jacinto-models

    This repository has moved. The new link can be obtained from https://github.com/TexasInstruments/jacinto-ai-devkit

    Mr.Paper/tidl-api

    Mr.Paper/PaddleSlim

    PaddleSlim is an open-source library for deep model compression and architecture search.

    Mr.Paper/Driver-Fatigue-Detection

    Detect driver drowsiness and gaze direction

    Mr.Paper/SSD-Tensorflow

    Single Shot MultiBox Detector in TensorFlow

    Mr.Paper/Fatigue-Driving-Detection-Alogorithm-Based-on-Deep-Learning

    Histogram of Oriented Gradient; convolutional neural network; fatigue driving detection

    Mr.Paper/model-compression

    model compression based on pytorch (1、quantization: 8/4/2bits(dorefa)、ternary/binary value(twn/bnn/xnor-net);2、 pruning: normal、regular and group convolutional pruning;3、 group convolution structure;4、BN fusion for binary value of feature(A))

    Mr.Paper/caffe-jacinto

    This repository has moved. The new link can be obtained from https://github.com/TexasInstruments/jacinto-ai-devkit

    Mr.Paper/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,近30万字。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

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