搜索资源列表
tensorflow-resnet-master
- 残差神经网络的代码，可以用，非常好，，，，，，。(resual CNN about deep learning ,very good.........................)
Tensorflow CNN
- 卷积神经网络识别手写数字，放在jupyter直接跑，99%识别率，已经和Tensorboard联通好了(Convolutional neural network recognizes handwritten numerals and runs directly on jupyter. The recognition rate is 99%. It has been connected with Tensorboard.)
卷积网络matlab实现
- 用卷积神经网络（CNN）进行人脸识别，matlab编程，可用。(Convolutional neural network (CNN) is used for face recognition, and MATLAB programming is available.)
DeepLearning_tutorials-master
- 深度学习工具包，内含多种CNN 算法，实验采用PYTHON为主要编程语言(The deep learning toolkit contains many CNN algorithms. PYTHON is used as the main programming language in the experiment.)
Face Recognition. From Traditional to Deep Learning Methods
- 近几年，传统的人脸识别算法被深度卷积网络所代替。CNN的主要优势就是可以结合庞大的数据集提取出原先所提出不出来的优质feature,与此同时精度也提升了很多。同时CNN的出现也加速了计算机视觉的发展，例如object detection 、recognition、segmentation。
Hardware-CNN-master
- Convolutional neural network code for fpga
hyperspectral-classification-with-svm-master
- svm高光谱图像分类3D-CNN Hyperspectral Image Classification(svmHyperspectral Image Classification)
classifier_cnn
- 以卷积神经网络对遥感数据（PaviaU）进行分类的一个算例，对于卷积神经网络的学习很有帮助。(An example of classification of remote sensing data (PaviaU) by convolution neural network is very helpful for the learning of convolution neural network.)
第 08 章 基于知识库的手写体数字识别
- 通过深度学习，利用已有库文件提取手写体图信息。与数据库中的内容进行对比，来识别手写体字母。(Through in-depth learning, handwritten graphic information is extracted from existing library files. Compare with the content in the database to recognize handwritten letters.)
AbnormalBehaviorDetection-master
- 基于光流特征的监控视频异常行为检测 使用CNN，RNN在UCSD数据库中实现 使用Keras，python3.6(Abnormal Behavior Detection of Monitoring Video Based on Optical Flow Characteristics)
tamper
- 用深度学习卷积网络CNN,实现图像复制粘贴和图像拼接篡改的定位(Using deep learning convolution network CNN to locate image copy-move and image splicing tampering)
卷积神经网络CNN进行图像分类
- 基于卷积神经网络的图像识别，应用于MATLAB(Image Recognition Based on Convolutional Upgrading Network)
matlab手写卷积神经网络人脸识别
- 基于卷积神经网络的人脸识别，学生作品啊啊啊啊啊啊(open face cnn student school what i should do)
flask-keras-cnn-image-retrieval-master
- 用于图像检索，很有用，数据库中仅包含少量图片，但是可运行，已经验证过了。(Useful for image retrieval. The database contains only a few pictures, but it can run and has been verified.)
object_detect.py
- 使用CNN检测目标 基于Tensorflow目标检测API(Uses CNN to detect objects. Based on Tensorflow Object Detection API)
models
- 包含unet/google-v2/CNN等多种神经网络的模型(Multiple Neural Network Models)
04.CNN处理CiFar
- 以python语言为基础，利用tensorflow机器学习架构，两层卷积神经网络实现，CiFar数据集图片分类功能。(Based on Python language, using tensorflow machine learning architecture, two-layer convolutional neural network, CiFar data set image classification function.)
cifar-10-cnn-master
- 经典数据集分类,利用卷积神经网络分类，利用python语言编写(classic picture classification)
dataset-master
- 深度学习进行调制识别的数据集，用于卷积神经网络(dataset for cnn include generate_RML2016.04c and generate_RML2016.10a)
DeepLearnToolbox-master
- CNN,DBN算法可以对手写体数字进行识别，准确率高(CNN and DBN algorithm can recognize handwritten numerals with high accuracy)