转载链接:https://www.jianshu.com/p/4e5b3e652639 Szegedy在2015年发表了论文Rethinking the Inception Architecture for Computer Vision,该论文对之前的Inception结构提出了多种优化方法,来达到尽可能高效的利用计算资源的目的.作者认为随意增大Inception的复杂度,后果就是Inception的错误率很容易飙升,还会成倍的增加计算量,所以必须按照一套合理的规则来优化Inception结构…
https://arxiv.org/abs/1512.00567 Convolutional networks are at the core of most state-of-the-art computer vision solutions for a wide variety of tasks. Since 2014 very deep convolutional networks started to become mainstream, yielding substantial gai…
目录 0. paper link 1. Overview 2. Four General Design Principles 3. Factorizing Convolutions with Large Filter Size 3.1 Factorization into smaller convolutions 3.2. Spatial Factorization into Asymmetric Convolutions 4. Utility of Auxiliary Classifiers…
1. 论文思想 factorized convolutions and aggressive regularization. 本文给出了一些网络设计的技巧. 2. 结果 用5G的计算量和25M的参数.With an ensemble of 4 models and multi-crop evaluation, we report 3.5% top-5 error and 17.3% top-1 error. 3. Introduction scaling up convolution netwo…
WTF is computer vision? Posted Nov 13, 2016 by Devin Coldewey, Contributor Next Story Someone across the room throws you a ball and you catch it. Simple, right? Actually, this is one of the most complex processes we've ever attempted to compr…
Analyzing The Papers Behind Facebook's Computer Vision Approach Introduction You know that company called Facebook? Yeah, the one that has 1.6 billion people hooked on their website. Take all of the happy birthday posts, embarrassing pictures of you…
The picture above is funny. But for me it is also one of those examples that make me sad about the outlook for AI and for Computer Vision. What would it take for a computer to understand this image as you or I do? I challenge you to think explicitly…
