搜索资源列表
mnist
- cnn 深度学习的库,最经典必用的训练资源
Tutorial_HYLee_GAN
- Introduction of Generative Adversarial Network (GAN)
Convolutional-Neural-Network-master
- matlab,深度学习工具箱,经典的卷积神经网络,共有两层卷积层。输入为28*28*1的图片(Matlab, the deep learning toolbox, the classic convolution neural network, has two volumes of layers. A picture entered into 28*28*1)
bp和maltab的车牌识别
- 实现了灰度处理,锐化,边缘检测,神经网络(Grayscale processing, sharpening, edge detection, neural network)
DeepLearnToolbox-master
- 集中经典的DeepLearning算法 CNN SAE DBN等(Deep Learning CNN SAE DBN Several classic DeepLearning algorithms CNN SAE DBN etc)
ChineseNER-master
- BiLSTM+CNN结构实现中文命名实体识别(implement Chinese NER with BiLSTM+CNN architecture)
people faces
- 用卷积神经网络(CNN)实现人脸识别,效果还可以,一个是training的程序,可以训练网络。一个是use程序,可以识别人脸(Using convolution neural network (CNN) to achieve face recognition, the effect is also available, one is the training program, can train the network. One is a use program that recognizes
CNN入门matlab程序
- matlab神经网络基础代码,包含各类神经网络代码和测试案例(Matlab neural network basic code, including various types of neural network code and test cases)
ConvolutionalNetwork-master
- 这是Convolutional Network的一个实现。此外,它提供了一些可视化更高级别特征的工具,并演示了原始输入图像重建的一个例子。(This is one of the implementations of Convolutional Network. In addition, it provides some tools for visualizing higher level features, and demonstrates an example of original inpu
market_evaluation
- 可以对已经训练好的CNN模型进行特征提取,并且对提取得到的图片特征进行性能识别(Feature extraction can be performed on the trained CNN model, and performance identification of the extracted image features can be performed.)
FaceNet-A-Unified-Embedding-for-Face-Recognition-and-Clustering
- FaceNet---深度学习与人脸识别的二次结合 Facenet是一个通用的系统,采用CNN神经网络将人脸图像映射到128维的欧几里得空间,我们可以根据两幅人像的欧几里得距离去判断两个人像的相似程度。两个人像之间的欧几里得距离越近,说明它们越相似。 FaceNet可以用于人脸验证(是否是同一人?),识别(这个人是谁?)和聚类(寻找类似的人?)。FaceNet采用的方法是通过卷积神经网络学习将图像映射到欧几里得空间。空间距离直接和图片相似度相关:同一个人的不同图像在空间距离很小,不同人的图像在
network
- 卷积神经网络函数,用于数据预测,分类以及识别(Convolution neural network functions for data prediction, classification and identification)
深度学习工具包matlab
- 深度学习matlab工具包 包括SAE DBN CNN 等matlab代码(Deep learning matlab tool kit includes SAE DBN CNN and other matlab code)
labelImg-master
- LabelImg 是一个可视化的图像标定工具。使用该工具前需配置环境python + lxml。Faster R-CNN,YOLO,SSD等目标检测网络所需要的数据集,均需要借此工具标定图像中的目标。(LabelImg is a visual image calibration tool. You need to configure the environment Python + lxml before using this tool. Faster R-CNN, YOLO, SSD and
richter-master
- 使用cnn + svm的分类,结果运行不错(Using CNN + SVM classification, the result runs pretty well.)
CNN_HSIC-master
- CNN高光谱图像分类,包含1D,2D,3D(CNN hyperspectral image classification)
CAE
- 卷积自编码器,深度学习中的CAE,类似CNN,是深度学习的基本框架之一(Convolution self encoder, CAE in depth learning, similar to CNN, is one of the basic frameworks for deep learning.)
BRATS-master
- # BRATS 2017 ## Brain Tumor Image Segmentation Challenge 2017 This is an approach for brain tumor segmentation based on a multi-path CNN. _________________________________________________________________________________________________________
Inception_V3(Transfer)
- 本算法实现了InceptionV3模型的迁移学习。训练好的inceptionV3模型可自行搜索下载.pb文件,数据集需为本地jpg图片。(Realization of full adder schematic diagram)
Verilog-Generator-of-Neural-Networks
- 利用DE0nano开发板实现了对用的卷积神经网络(The CNN algorithm is implemented.based FPGA)