A method for performing size K×K max pooling with stride S at a pooling layer of a convolutional neural network to downsample input data includes receiving input data, buffering the input data, applying a cascade of size 2×2 pooling stages to the buffered input data to generate downsampled...
[2] Springenberg J T, Dosovitskiy A, Brox T, et al. Striving for Simplicity: The All Convolutional Net[J]. Eprint Arxiv, 2014. [3] Zhang X, Zhou X, Lin M, et al. ShuffleNet: An Extremely Efficient Convolutional Neural Network for Mobile Devices[J]. 2017. 阿里天池模型结构设计与优...
Deep learning10is a branch of machine learning that leverages multi-layer neural network models to efficiently learn and represent complex data. In recent years, deep learning has made revolutionary breakthroughs in fields such as computer vision, natural language processing, and speech recognition, sur...
原文链接:[[2101.08170] SUGAR: Subgraph Neural Network with Reinforcement Pooling and Self-Supervised Mutual Information Mechanism (arxiv.org)](https://arxiv.org/abs/2101.08170) 一、动机 判别性:现有的方法大多融合了所有的结构特征和节点属性来得到图的整体表征,忽略了更精细的子结构的语义,带来潜在的过...
In this paper we present a deep neural network topology that incorporates asimple to implement transformation invariant pooling operator (TI-POOLING).This operator is able to efficiently handle prior knowledge on nuisancevariations in the data, such as rotation or scale changes. Most current methodsus...
Time pooling and correlation in artificial neural networks PROBLEM TO BE SOLVED: To provide a calculation method for operating a hierarchical artificial neural network (ANN). A single correlator has two or more con... スコット,ジョン,キャンプベル,イマイノ,ウェイン,イサミ,オズカン,アー...
Global covariance pooling in convolutional neural networks has achieved impressive improvement over the classical first-order pooling. Recent works have shown matrix square root normalization plays a central role in achieving state-of-the-art performance. However, existing methods depend heavily on eigende...
The Pytorch implementation for the NeurIPS2019 paper of "Gaussian-Based Pooling for Convolutional Neural Networks" by Takumi Kobayashi.CitationIf you find our project useful in your research, please cite it as follows:@inproceedings{kobayashi2019neurips, title={Gaussian-Based Pooling for Convolutional Ne...
In most convolution neural networks (CNNs), downsampling hidden layers is adopted for increasing computation efficiency and the receptive field size. Such operation is commonly so-called pooling. Maximation and averaging over sliding windows (max/average pooling), and plain downsampling in the form...
本人精读了事件抽取领域的经典论文《Event Extraction via Dynamic Multi-Pooling Convolutional Neural Network》,并作出我的读书报告。这篇论文由中科院自动化所赵军、刘康等人发表于ACL2015会议,提出了用CNN模型解决事件抽取任务。 在深度学习没有盛行之前,解决事件抽取任务的传统方法,依赖于较为精细的特征设计已经一系列...