Section 2 provides a brief overview of AI concepts that are heavily utilized in DL. CNNs and CapsNets are discussed in 3 Convolutional Neural Networks (CNNs), 4 Capsule Networks (CapsNet) respectively. The structure, implementations and performance evaluation methods are reviewed in Section 5 ...
CVPR2019包含了多个与胶囊网络相关的教程,本文介绍其中Yogesh Rawat的一篇综述PPT《Capsule Networks: A Survey》,其内容大致如下: 简介 早期工作 基础工作 视频胶囊 路由 动态和EM 注意力 多模态 通用 快速动态路由 模态 视觉:图像和视频 文本 图 3D点云 问题领域 分类 分割 定位 应用 关系抽取 对抗检测 脑瘤分类...
Symbolic Artificial Intelligence with its hard coding rules is incapable of solving these complex problems resulting in the introduction of Deep Learning (DL) models such as Recurrent Neural Networks and Convolutional Neural Networks (CNN). However, CNNs require lots of training data and are ...
Routing enhancement in wireless sensor networks based on capsule networks: A surveydoi:10.22075/ijnaa.2022.6325Abdullah, Hussein JawadAbdullah, Mohammed NajmInternational Journal of Nonlinear Analysis & Applications
Patrick Mensah Kwabena, Adekoya Adebayo Felix, Mighty Ayidzoe Abra, Edward Baagyire Y (2022) Capsule networks-a survey. J King Saud Univ-Comput Inf Sci 34(1):1295–1310 Google Scholar Paymode Ananda S, Malode Vandana B (2022) Transfer learning for multi-crop leaf disease image classific...
CapsNets, an evolution in the field of deep learning, provide a unique framework for image analysis that is particularly suited for medical imaging tasks. Unlike traditional convolutional neural networks (CNNs) that may lose spatial hierarchies between high-level features, CapsNets preserve these ...
Under a Creative Commons license open accessAbstract Capsule Networks (CapsNets) preserve the hierarchical spatial relationships between objects, and thereby bear the potential to surpass the performance of traditional Convolutional Neural Networks (CNNs) in performing tasks like image classification. This ...
Howard, A. G., Zhu, M. & Chen, B. MobileNets: Efficient convolutional neural networks for mobile vision applications (2017). He, K., Zhang, X. & Ren, S. Deep residual learning for image recognition. In 2016 IEEE Conference on Computer Vision and Pattern Recognition (2016). Chen, P....
Text classification is an important and classical problem in natural language processing. There have been a number of studies that applied convolutional neural networks (convolution on regular grid, e.g., sequence) to classification. However, only a limited number of studies have explored the more ...
Capsule Networks 传统CNN: 工作原理:将每一层对应的特征累积起来,从寻找边缘开始,然后是形状、再识别实际的对象。 (1)然而,在这个过程中,所有这些特征的空间关系信息丢失了。 (2)对图片的角度要求有点苛刻,它能容忍照片稍微旋转一些,但要是旋转太多,它就不认得了。(旋转的程度超出了最大池化(maxpooling)所带来...