476 Open source projects that are alternatives of or similar to modified_refinedet

A review of change detection methods, including codes and open data sets for deep learning. From paper: change detection based on artificial intelligence: state-of-the-art and challenges.

Domain Guided Dropout for Person Re-identification

Convert image folder to lmdb, adapted from Efficient-PyTorch

A realistic simulator for a 3D printer motion controller

Weakly-Supervised Semantic Segmentation Network with Deep Seeded Region Growing (CVPR 2018).

educational repo for storing everything I do with embedded systems (uC's, SoC's, FPGA, & CPLD) including solutions to online courses I take

Simple implementation of kpzhang93's paper from Matlab to c++, and don't change models.

Implemetation of Pyramid Scene Parsing Network in Pytorch

通用深度学习推理服务，可在生产环境中快速上线由TensorFlow、PyTorch、Caffe框架训练出的深度学习模型。

theCore: C++ embedded framework

Minimalist plugin manager for GDB and LLDB

Auto-ReID and Other Person Re-Identification Projects

🎯 保姆级深度学习从入门到放弃 🤪 🤪

802.15.4 experiments with nRF52840

XNOR-Net, CUDNN5 supported version of XNOR-Net-caffe: https://github.com/loswensiana/BWN-XNOR-caffe

Squeeze-and-Excitation Networks

Re-implementation of tripletloss function in FaceNet

Automatic colorization using deep neural networks. "Colorful Image Colorization." In ECCV, 2016.

Caffe implementation for "Guided Optical Flow Learning"

ID-discriminative Embedding (IDE) for Person Re-identification

NFC smart cards and payment terminals in Nigeria

Oriented Response Networks, in CVPR 2017

Mxnet2Caffe_Tensor RT

MTCNN with Motion Detection, on Raspberry Pi with Love

基于RabbitMQ简单实现验证码识别平台，训练网络模型智能识别图形验证码

A tool that automates booting of operating systems on target hardware or in qemu

Automatic image captioning model based on Caffe, using features from bottom-up attention.

The SimNets Architecture's Implementation in Caffe

Embedded Linux Education Kit

Xception implemented with caffe

A Big Awesome List CoreML Models.

Semantic Image Segmentation by Scale-Adaptive Networks (TIP 2019)

Compact Generalized Non-local Network (NIPS 2018)

No description or website provided.

Implementation based on the paper Li et al., “A Convolutional Neural Network Cascade for Face Detection, ” 2015 CVPR

VGG16 architecture with BatchNorm

The Convolutional Neural Network(CNN) for Android

Depth Map Super-Resolution by Deep Multi-Scale Guidance, ECCV 2016

Reimplement RetinaFace use C++ and TensorRT

PCB designs for Battman lithium ion battery management system

Caffe for Sparse Convolutional Neural Network

No description or website provided.

Caffe2 on iOS Real-time Demo. Test with Your Own Model and Photos.

Semantically consistent regularizer for zero-shot learning

A windows caffe implementation of YOLO detection network

FullMetalUpdate Python client application.

Deep learning software for colorizing black and white images with a few clicks.

Caffe-to-Keras weight converter. Can also export weights as Numpy arrays for further processing.

Supervised Semantics-preserving Deep Hashing (TPAMI18)

This app recognises 3 hand signs - fist, high five and victory hand [ rock, paper, scissors basically :) ] with live feed camera. It uses a HandSigns.mlmodel which has been trained using Custom Vision from Microsoft.

Visualizer for neural network, deep learning, and machine learning models

Spying on Microcontrollers using Current Sensing and embedded TinyML models

MTCNN Face Detection & Alignment

A Caffe Implementation of SRGAN

Python layer for the Caffe deep learning framework to compute the accuracy and the confusion matrix.

Multi-layer Recurrent Neural Networks (with LSTM) for character-level language models in Caffe

arcface and retinaface model convert mxnet to onnx.

A demo of using socket.io + backbone.js to create a simple chatroom service.

在caffe应用到工程实现时，为了方便系统安装，需要尽可能减少软件的依赖库。 本项目以bash shell/PowerShell脚本实现将caffe依赖的所有第三方库与caffe静态编译一起，以满足全静态编译的要求。 通过本项目提供的脚本生成的caffe编译环境不需要在系统安装任何第三方库和软件，就可以自动完成caffe项目静态编译. 目前在centos6.5/ubuntu16/win7/win10上测试通过,windows上VS2013,VS2015,MinGW 5.2.0编译通过

Generate API documentation from Markdown