PP: Triple-shapelet networks for time series classification

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PP: Triple-shapelet networks for time series classification

Problem: time series classification shapelet-based method: two issues 1. for multi-class imbalanced classification tasks, these methods will ignore the shapelets that can distinguish minority class from other classes. 2. the shapelets are fixed after…

How to Use Convolutional Neural Networks for Time Series Classification

How to Use Convolutional Neural Networks for Time Series Classification 2019-10-08 12:09:35 This blog is from: https://towardsdatascience.com/how-to-use-convolutional-neural-networks-for-time-series-classification-56b1b0a07a57 Introduction A large am…

PP: Extracting statisticla graph features for accurate and efficient time series classification

Problem: TSC, time series classification; Traditional TSC: find global similarities or local patterns/subsequence(shapelet). We extract statistical features from VG to facilitate TSC Introduction: Global similarity: the difference between TSC and oth…

不平衡数据下的机器学习方法简介 imbalanced time series classification

imbalanced time series classification http://www.vipzhuanli.com/pat/books/201510229367.5/2.html?page=2 这个专利可以去国家专利局网站查询,有具体文档. https://www.jianshu.com/p/3e8b9f2764c8 机器学习已经成为了当前互联网领域不可或缺的技术之一,前辈们对机器学习模型的研究已经给我们留下了一笔非常宝贵的财富,然而在工业界的应用中我们可以看到,应用场景千千万万,数…

《Generative Adversarial Networks for Hyperspectral Image Classification 》论文笔记

论文题目:<Generative Adversarial Networks for Hyperspectral Image Classification> 论文作者:Lin Zhu, Yushi Chen, Member, IEEE, Pedram Ghamisi, Member, IEEE, and Jó n Atli Benediktsson, Fellow, IEEE 论文发表时间:2018 网络简称:3D-GAN 发表期刊:IEEE Transactions on Geoscience…

PP: Modeling extreme events in time series prediction

KDD: Knowledge Discovery and Data Mining (KDD) Insititute: 复旦大学,中科大 Problem: time series prediction; modelling extreme events; overlook the existence of extreme events, which result in weak performance when applying them to real time series. 为什么研究ext…

PP: Composite visual mapping for time series visualization

However: The conventional visual mapping maps each data attribute onto a single visual channel Purpose: investigate composite visual mapping综合可视映射: mapping single data attributes onto several visual channels. a valuable tool for understanding those r…

describe neural networks as a series of computational steps via a directed graph.

https://www.microsoft.com/en-us/research/product/cognitive-toolkit/ https://github.com/microsoft/cntk https://github.com/Microsoft/CNTK/blob/master/README.md…

Hyperspectral Image Classification Using Similarity Measurements-Based Deep Recurrent Neural Networks

用RNN来做像素分类,输入是一系列相近的像素,长度人为指定为l,相近是利用像素相似度或是范围相似度得到的,计算个欧氏距离或是SAM. 数据是两个高光谱数据 1.Pavia University,Reflective Optics System Imaging Spectrometer (ROSIS) sensor得到,102个波段,1.3米空间分辨率,总大小610*340像素,9类地物 2.Salinas image,Airborne Visible/Infrared Imaging Spect…

AlexNet论文翻译-ImageNet Classification with Deep Convolutional Neural Networks

ImageNet Classification with Deep Convolutional Neural Networks 深度卷积神经网络的ImageNet分类 Alex Krizhevsky University of Toronto 多伦多大学 kriz@cs.utoronto.ca Ilya Sutskever University of Toronto 多伦多大学 ilya@cs.utoronto.ca Geoffrey E. Hinton University of Toront…