The Development of CNN Architectures: From LeNet to EfficientNet

The Development of CNN Architectures: From LeNet to EfficientNet

Author: zzq https://zhuanlan.zhihu.com/p/68411179 This article is authorized, and unauthorized reproduction is not allowed. Introduction to Basic Components of CNN 1. Local Receptive Field In images, the connections between local pixels are relatively tight, while the connections between distant pixels are weaker. Therefore, each neuron does not need to perceive the entire image globally; it only … Read more

Designing CNN Networks: NAS vs Handcraft

Designing CNN Networks: NAS vs Handcraft

Click the blue text above to follow us! When training a Convolutional Neural Network (CNN), it is common to first select a well-known backbone (such as ResNet-50) and then adjust the architecture to balance performance and efficiency based on requirements. Often, this adjustment concept relies heavily on experience, which needs to be cultivated through extensive … Read more

Significantly Improve Image Recognition Network Efficiency: Facebook’s IdleBlock Hybrid Composition Method

Significantly Improve Image Recognition Network Efficiency: Facebook's IdleBlock Hybrid Composition Method

Selected from arXiv Authors:Bing Xu, Andrew Tulloch, Yunpeng Chen, Xiaomeng Yang, Lin Qiao Compiled by Machine Heart Recently, Facebook AI proposed a new convolutional module called IdleBlock and a Hybrid Composition (HC) method using this module. Experiments show that this simple new method not only significantly improves network efficiency but also surpasses most neural architecture … Read more