FT-FVC: fast transformation-based feature vector concatenation for time series classification
Published 2023 View Full Article
- Home
- Publications
- Publication Search
- Publication Details
Title
FT-FVC: fast transformation-based feature vector concatenation for time series classification
Authors
Keywords
-
Journal
APPLIED INTELLIGENCE
Volume -, Issue -, Pages -
Publisher
Springer Science and Business Media LLC
Online
2023-01-12
DOI
10.1007/s10489-022-04386-3
References
Ask authors/readers for more resources
Related references
Note: Only part of the references are listed.- Learning-based shapelets discovery by feature selection for time series classification
- (2022) Jiahui Chen et al. APPLIED INTELLIGENCE
- SelfMatch: Robust semisupervised time‐series classification with self‐distillation
- (2022) Huanlai Xing et al. INTERNATIONAL JOURNAL OF INTELLIGENT SYSTEMS
- Wearable multi-sensor data fusion approach for human activity recognition using machine learning algorithms
- (2022) B Vidya et al. SENSORS AND ACTUATORS A-PHYSICAL
- HIVE-COTE 2.0: a new meta ensemble for time series classification
- (2021) Matthew Middlehurst et al. MACHINE LEARNING
- TS-CHIEF: a scalable and accurate forest algorithm for time series classification
- (2020) Ahmed Shifaz et al. DATA MINING AND KNOWLEDGE DISCOVERY
- ROCKET: exceptionally fast and accurate time series classification using random convolutional kernels
- (2020) Angus Dempster et al. DATA MINING AND KNOWLEDGE DISCOVERY
- Invariant subspace learning for time series data based on dynamic time warping distance
- (2020) Huiqi Deng et al. PATTERN RECOGNITION
- InceptionTime: Finding AlexNet for time series classification
- (2020) Hassan Ismail Fawaz et al. DATA MINING AND KNOWLEDGE DISCOVERY
- Small Data Challenges in Big Data Era: A Survey of Recent Progress on Unsupervised and Semi-Supervised Methods
- (2020) Guo-Jun Qi et al. IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE
- Deep learning for time series classification: a review
- (2019) Hassan Ismail Fawaz et al. DATA MINING AND KNOWLEDGE DISCOVERY
- Optimizing shapelets quality measure for imbalanced time series classification
- (2019) Qiuyan Yan et al. APPLIED INTELLIGENCE
- CLR-based deep convolutional spiking neural network with validation based stopping for time series classification
- (2019) Anjali Gautam et al. APPLIED INTELLIGENCE
- FastEE: Fast Ensembles of Elastic Distances for time series classification
- (2019) Chang Wei Tan et al. DATA MINING AND KNOWLEDGE DISCOVERY
- A survey on semi-supervised learning
- (2019) Jesper E. van Engelen et al. MACHINE LEARNING
- Semi-supervised time series classification on positive and unlabeled problems using cross-recurrence quantification analysis
- (2018) Lucas de Carvalho Pagliosa et al. PATTERN RECOGNITION
- Time Alignment Measurement for Time Series
- (2018) Duarte Folgado et al. PATTERN RECOGNITION
- Time Series Classification with HIVE-COTE
- (2018) Jason Lines et al. ACM Transactions on Knowledge Discovery from Data
- Time series feature learning with labeled and unlabeled data
- (2018) Haishuai Wang et al. PATTERN RECOGNITION
- Self-labeling techniques for semi-supervised time series classification: an empirical study
- (2017) Mabel González et al. KNOWLEDGE AND INFORMATION SYSTEMS
- The great time series classification bake off: a review and experimental evaluation of recent algorithmic advances
- (2016) Anthony Bagnall et al. DATA MINING AND KNOWLEDGE DISCOVERY
- The BOSS is concerned with time series classification in the presence of noise
- (2014) Patrick Schäfer DATA MINING AND KNOWLEDGE DISCOVERY
- Non-isometric transforms in time series classification using DTW
- (2014) Tomasz Górecki et al. KNOWLEDGE-BASED SYSTEMS
- Classification of time series by shapelet transformation
- (2013) Jon Hills et al. DATA MINING AND KNOWLEDGE DISCOVERY
- A time series forest for classification and feature extraction
- (2013) Houtao Deng et al. INFORMATION SCIENCES
- Using derivatives in time series classification
- (2012) Tomasz Górecki et al. DATA MINING AND KNOWLEDGE DISCOVERY
Find Funding. Review Successful Grants.
Explore over 25,000 new funding opportunities and over 6,000,000 successful grants.
ExploreDiscover Peeref hubs
Discuss science. Find collaborators. Network.
Join a conversation