DL之AlexNet：利用卷积神经网络类AlexNet实现猫狗分类识别(图片数据增强→保存h5模型)（一）
利用卷积神经网络类AlexNet实现猫狗分类识别(图片数据增强→保存h5模型)设计思路处理过程及结果呈现Found 17500 images belonging to 2 classes.Found 7500 images belonging to 2 classes.________________________________________________________________....
DL：深度学习算法(神经网络模型集合)概览之《THE NEURAL NETWORK ZOO》的中文解释和感悟（九）
DRN Deep residual networks (DRN) are very deep FFNNs with extra connections passing input from one layer to a later layer (often 2 to 5 layers) as well as the next layer. Instead....
DL：深度学习算法(神经网络模型集合)概览之《THE NEURAL NETWORK ZOO》的中文解释和感悟（八）
ELM Extreme learning machines (ELM) are basically FFNNs but with random connections. They look very similar to LSMs and ESNs, but they are not recurrent nor spiking. They also do....
DL：深度学习算法(神经网络模型集合)概览之《THE NEURAL NETWORK ZOO》的中文解释和感悟（七）
DCIGN Deep convolutional inverse graphics networks (DCIGN) have a somewhat misleading name, as they are actually VAEs but with CNNs and DNNs for the respective encoders an....
DL：深度学习算法(神经网络模型集合)概览之《THE NEURAL NETWORK ZOO》的中文解释和感悟（六）
DBN Deep belief networks (DBN) is the name given to stacked architectures of mostly RBMs or VAEs. These networks have been shown to be effectively trainable stack by stack, where ....
DL：深度学习算法(神经网络模型集合)概览之《THE NEURAL NETWORK ZOO》的中文解释和感悟(五)
MC Markov chains (MC or discrete time Markov Chain, DTMC) are kind of the predecessors to BMs and HNs. They can be understood as follows: from this node where I am now, what are ....
DL：深度学习算法(神经网络模型集合)概览之《THE NEURAL NETWORK ZOO》的中文解释和感悟(三)
AE Autoencoders (AE) are somewhat similar to FFNNs as AEs are more like a different use of FFNNs than a fundamentally different architecture. The basic idea behind autoencoders is....
DL：深度学习算法(神经网络模型集合)概览之《THE NEURAL NETWORK ZOO》的中文解释和感悟(二)
Feed forward neural networks (FF or FFNN) and perceptrons (P) are very straight forward, they feed information from the front to the back (input and output, respectively). Neural networks are often d....
DL：深度学习算法(神经网络模型集合)概览之《THE NEURAL NETWORK ZOO》的中文解释和感悟(一)
THE NEURAL NETWORK ZOOPOSTED ON SEPTEMBER 14, 2016 BY FJODOR VAN VEEN With new neural network architectures popping up every now and then, it’s hard to keep track of them all. Kn....
DL：神经网络算法简介之耗算力的简介、原因、经典模型耗算力计算、GPU使用之详细攻略
神经网络算法耗算力的简介 通过比特币来理解算力。算力（也称哈希率）是比特币网络处理能力的度量单位。即为计算机（CPU）计算哈希函数输出的速度。比特币网络必须为了安全目的而进行密集的数学和加密相关操作。 例如，当网络达到10Th/s的哈希率时，意味着它可以每秒进行10万亿次计算。神经网络算法耗算力的原因 ....
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