大概浏览了一下Multi-Scale Convolutional Neural Networks for Time Series Classification这篇论文(下图为模型),我理解这样一种方法就是类似于不断降采样,投入模型训练的过程,可能是不断二分,也可能是简单地进行一次二分就投入模型,总之是不同“分辨率”下对数据的处理训练 【2.2.3. Intermediate Supervision(中继监督...
Time series classification(TSC)has attracted various attention in the community of machine learning and data mining and has many successful applications such as fault detection and product identification in the process of building a smart factory.However,it is still challenging for the efficiency and ...
OMNI-SCALE CNNS: A SIMPLE AND EFFECTIVE KERNEL SIZE CONFIGURATION FOR TIME SERIES CLASSIFICATION 论文链接: https://openreview.net/forum?id=PDYs7Z2XFGv代码链接: https://github.com/Wensi-Tang/OS-CNN 摘要 感受野(RF)大小一直是影响一维卷积神经网络(1D-CNN)时间序列分类任务的重要因素之一。为了选择合适...
There are many methods for time series classification. Most of them consist of two major stages: on the first stage you either use some algorithm for measuring the difference between time series that you want to classify (dynamic time warping is a well-known one) or you use whatever tools ...
题目:TimeNet: Pre-trained deep recurrent neural network for time series classification 名称:TimeNet:用于时间序列分类的预训练深度循环神经网络 论文:arxiv.org/abs/1706.0883 代码:github.com/paudan/TimeN 38.GCN系列 GCN 题目:Spectral Networks and Locally Connected Networks on Graphs 名称:图上的谱网络...
下图是借用CNN处理文本处理的框架,并在图上做了修改,A Sensitivity Analysis of (and Practitioners' Guide to) Convolutional Neural Networks for Sentence Classification: 在这个框架中,卷积运算的维度从上文介绍的图片分类的2维空间信息转变为1维时间信息。而横向(d=5)的数据是同一类别的量化因子,作为描述同一时间...
ROCKET系列 ROCKET: Exceptionally fast and accurate time series classification using random convolutional ...
Rectified Linear Unit (ReLU for short) Pooling layers Fully connected layers This section dives into the definition of each one of these components through the example of the following example of classification of a handwritten digit. Architecture of the CNNs applied to digit recognition (source) ...
cnn_stride, dropout_rate, num_classes): self.time_series_length = time_series_length ...
2,'Stride',2) fullyConnectedLayer(10) softmaxLayer classificationLayer]; % 定义训...