DeepTracker: Visualizing the Training Process of Convolutional Neural Networks（对卷积神经网络训练过程的可视化）

前段时间一直在关注 CNN 的实现,查看了 caffe 的代码以及 convnet2 的代码.目前对单机多卡的内容比较感兴趣,因此特别关注 convnet2 关于 multi-GPU 的支持. 其中 cuda-convnet2 的项目地址发布在:Google Code:cuda-convnet2 关于 multi-GPU 的一篇比较重要的论文就是:One weird trick for parallelizing convolutional neural networks 本文也将针对这篇文章给

Adit Deshpande CS Undergrad at UCLA ('19) Blog About A Beginner's Guide To Understanding Convolutional Neural Networks Introduction Convolutional neural networks. Sounds like a weird combination of biology and math with a little CS sprinkled in, but

Table of Contents: Architecture Overview ConvNet Layers Convolutional Layer Pooling Layer Normalization Layer Fully-Connected Layer Converting Fully-Connected Layers to Convolutional Layers ConvNet Architectures Layer Patterns Layer Sizing Patterns C

A Beginner's Guide To Understanding Convolutional Neural Networks Introduction Convolutional neural networks. Sounds like a weird combination of biology and math with a little CS sprinkled in, but these networks have been some of the most influential

About this Course This course will teach you how to build convolutional neural networks and apply it to image data. Thanks to deep learning, computer vision is working far better than just two years ago, and this is enabling numerous exciting applica

Adit Deshpande CS Undergrad at UCLA ('19) Blog About A Beginner's Guide To Understanding Convolutional Neural Networks Part 2 Introduction Link to Part 1 In this post, we’ll go into a lot more of the specifics of ConvNets. Disclaimer: Now, I do reali

Image Scaling using Deep Convolutional Neural Networks This past summer I interned at Flipboard in Palo Alto, California. I worked on machine learning based problems, one of which was Image Upscaling. This post will show some preliminary results, dis

When we hear about Convolutional Neural Network (CNNs), we typically think of Computer Vision. CNNs were responsible for major breakthroughs in Image Classification and are the core of most Computer Vision systems today, from Facebook's automated pho

Convolutional Neural Networks Convolutional Neural Networks are made up of neurons that have learnable weights and biases. Each neuron receives some inputs, performs a dot product and optionally follows it with a non-linearity. They still have a loss