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Caffe: a fast open framework for deep learning.
This fork of BVLC/Caffe is dedicated to improving performance of this deep learning framework when running on CPU, in particular Intel® Xeon processors (HSW+) and Intel® Xeon Phi processors
fork from https://github.com/yjxiong/caffe
:heart::coffee: Deep Learning of Binary Hash Codes for Fast Image Retrieval (CVPRW15)
:crown: Supervised Semantics-preserving Deep Hashing (SSDH)
Facial keypoints extraction using Caffe
Caffe fork that supports Fast R-CNN
LSTM implementation on Caffe
Data in HDF5 format
caffe pretrained models and prototxt
OCR with caffe deep learning framework
Proof of concept prototype to perform distributed training using BVLC/caffe, based on a parameter server implementation using MPI. Data parallelism only
Caffe branch for R-FCN
Speech Recognition with the Caffe deep learning framework, migrating to
Caffe Windows with realtime data augmentation
Caffe for YOLOv2 & YOLO9000
This is currently an experimental refactoring of Caffe.
Caffe使用教程
主流ocr算法研究实验性的项目,目前实现了CNN+BLSTM+CTC架构
Evaluation of the CNN design choices performance on ImageNet-2012.
Line based ATR Engine based on OCRopy
Pretrained mixed models to be used with Calamari.
A Keras implementation of CapsNet in NIPS2017 paper "Dynamic Routing Between Capsules". Now Val_acc>99.5%.
A Tensorflow implementation of CapsNet(Capsules Net) in Hinton's paper Dynamic Routing Between Capsules
本项目可以用来调用 https://github.com/kerlomz/captcha_trainer 项目训练的模型,使用TensorFlowSharp写的调用模型代码。
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