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Time Series Clustering and Classification最新文献

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Feature-based approaches 基于特征的方法
Time Series Clustering and Classification Pub Date : 2019-03-19 DOI: 10.1201/9780429058264-9
E. Maharaj, P. D’Urso, Jorge Caiado
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引用次数: 0
Other time series clustering approaches 其他时间序列聚类方法
Time Series Clustering and Classification Pub Date : 2019-03-19 DOI: 10.1201/9780429058264-8
E. Maharaj, P. D’Urso, Jorge Caiado
{"title":"Other time series clustering approaches","authors":"E. Maharaj, P. D’Urso, Jorge Caiado","doi":"10.1201/9780429058264-8","DOIUrl":"https://doi.org/10.1201/9780429058264-8","url":null,"abstract":"","PeriodicalId":270319,"journal":{"name":"Time Series Clustering and Classification","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2019-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131610445","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Observation-based clustering 基于聚类
Time Series Clustering and Classification Pub Date : 2019-03-19 DOI: 10.1201/9780429058264-5
E. Maharaj, P. D’Urso, Jorge Caiado
{"title":"Observation-based clustering","authors":"E. Maharaj, P. D’Urso, Jorge Caiado","doi":"10.1201/9780429058264-5","DOIUrl":"https://doi.org/10.1201/9780429058264-5","url":null,"abstract":"","PeriodicalId":270319,"journal":{"name":"Time Series Clustering and Classification","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2019-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129279434","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Fuzzy clustering 模糊聚类
Time Series Clustering and Classification Pub Date : 2019-03-19 DOI: 10.1201/9780429058264-4
E. Maharaj, P. D’Urso, Jorge Caiado
{"title":"Fuzzy clustering","authors":"E. Maharaj, P. D’Urso, Jorge Caiado","doi":"10.1201/9780429058264-4","DOIUrl":"https://doi.org/10.1201/9780429058264-4","url":null,"abstract":"フ ァ ジ ィ ・ク ラス タ リン グ (Fuzzy Clustering) 有限個の個体に つ い て の 多変量デ ー タが 与えられたとき、これらの 個体を互い に重なりあわない い くつ か の クラス に分 け、同じクラス に はい る個体はJhl い !こ距離が近く、 異なるクラス に はい る個体は距離が遠い ように分類することをクラス タリン グとい う。ファ ジィ ・クラス タリン グ とは、通 常 、 次 の A 、 B の い ずれ か を意味する。 A .クリス プ分割 (共通部分が 空 で、すべ ての合併が個体全体 の 集合に致するような部分集合の 族の こと、分類ともい う。 )の 代りにファジィ分割を利用す るもの 。B .個体の 集合上 の フ ァ ジィ同値関係をデ ータから構成するもの 。 A とB につ い て代表的な手法 を次に挙げる。 A .(Fuzzy c −means )n 個の個体に つ い て の データが γ 次元 空間 の点 褊 k = 1,.., 12,で 表されるとする。 c 個の ファ ジィ集合からなるファジィ分割とは、ΣtUi(x ,) =1, k=1,..,n ,を満たすIti, i =・1,..,c,を意味する。ファジィ分 割を決定 するため 、晦 μ、(κh)に関する最適化問題 :min Σ tk (eq・,) II Xh− Vi ll Z (Il Ilは L2ノル ム )を解く。 ここで、最適化は 砺 i= 1 , ..,c;k ; 1,..,n ,および Vi, i=一1,..,・c,につ い て行う。 制約条件として 、 晦 が ファジィ分割を表わすように、 0≦ 晦 ≦Lfor a1141e ;Σ、 uilt =1, for all k,が 課せ られる。また、 m は m > 1 となる指数 ラメータである。 Bezdek","PeriodicalId":270319,"journal":{"name":"Time Series Clustering and Classification","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2019-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122725529","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 2
Model-based clustering 基于模型的聚类
Time Series Clustering and Classification Pub Date : 2019-03-19 DOI: 10.1201/9780429058264-7
E. Maharaj, P. D’Urso, Jorge Caiado
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引用次数: 0
Time series features and models 时间序列特征和模型
Time Series Clustering and Classification Pub Date : 2019-03-19 DOI: 10.1201/9780429058264-2
E. Maharaj, P. D’Urso, Jorge Caiado
{"title":"Time series features and models","authors":"E. Maharaj, P. D’Urso, Jorge Caiado","doi":"10.1201/9780429058264-2","DOIUrl":"https://doi.org/10.1201/9780429058264-2","url":null,"abstract":"","PeriodicalId":270319,"journal":{"name":"Time Series Clustering and Classification","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2019-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125060529","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Traditional cluster analysis 传统聚类分析
Time Series Clustering and Classification Pub Date : 2019-03-19 DOI: 10.1201/9780429058264-3
E. Maharaj, P. D’Urso, Jorge Caiado
{"title":"Traditional cluster analysis","authors":"E. Maharaj, P. D’Urso, Jorge Caiado","doi":"10.1201/9780429058264-3","DOIUrl":"https://doi.org/10.1201/9780429058264-3","url":null,"abstract":"","PeriodicalId":270319,"journal":{"name":"Time Series Clustering and Classification","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2019-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127898700","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Feature-based clustering 基于特征聚类
Time Series Clustering and Classification Pub Date : 2019-03-19 DOI: 10.1201/9780429058264-6
E. Maharaj, P. D’Urso, Jorge Caiado
{"title":"Feature-based clustering","authors":"E. Maharaj, P. D’Urso, Jorge Caiado","doi":"10.1201/9780429058264-6","DOIUrl":"https://doi.org/10.1201/9780429058264-6","url":null,"abstract":"","PeriodicalId":270319,"journal":{"name":"Time Series Clustering and Classification","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2019-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115495969","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Software and data sets 软件和数据集
Time Series Clustering and Classification Pub Date : 2019-03-19 DOI: 10.1201/9780429058264-11
Yi Wang, Nassim Ait Ali Braham, Zhitong Xiong, Chenying Liu, C. Albrecht, Xiaoxiang Zhu
{"title":"Software and data sets","authors":"Yi Wang, Nassim Ait Ali Braham, Zhitong Xiong, Chenying Liu, C. Albrecht, Xiaoxiang Zhu","doi":"10.1201/9780429058264-11","DOIUrl":"https://doi.org/10.1201/9780429058264-11","url":null,"abstract":"S elf-supervised pretraining bears the potential to generate expressive representations from large-scale Earth observation (EO) data without human annotation. However, most existing pretraining in the field is based on ImageNet or medium-sized, labeled remote sensing (RS) datasets. In this article, we share an unlabeled dataset Self-Supervised Learning for Earth Observa-tion-Sentinel-1/2 ( SSL4EO - S12 ) to assemble a large-scale, global, multimodal, and multiseasonal corpus of satellite imagery. We demonstrate SSL4EO-S12 to succeed in self-supervised pretraining for a set of representative methods: momentum contrast (MoCo), self-distillation with no labels (DINO), masked autoencoders (MAE), and data2vec, and multiple downstream applications, including scene classification, semantic segmentation, and change detection. Our benchmark results prove the effectiveness of SSL4EO-S12 compared to existing datasets. The dataset, related source code, and pretrained models are available at https://github.com/zhu-xlab/ SSL4EO-S12.","PeriodicalId":270319,"journal":{"name":"Time Series Clustering and Classification","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2019-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114265057","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Other time series classification approaches 其他时间序列分类方法
Time Series Clustering and Classification Pub Date : 2019-03-19 DOI: 10.1201/9780429058264-10
E. Maharaj, P. D’Urso, Jorge Caiado
{"title":"Other time series classification approaches","authors":"E. Maharaj, P. D’Urso, Jorge Caiado","doi":"10.1201/9780429058264-10","DOIUrl":"https://doi.org/10.1201/9780429058264-10","url":null,"abstract":"","PeriodicalId":270319,"journal":{"name":"Time Series Clustering and Classification","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2019-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115941801","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
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