Univariate time series classification using information geometry
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
The ability of GeAN to learn the temporal interactions embedded in the node and edge features of graphs in their native formats solves the shortcomings associated with using separate feature extraction processes to capture temporal and spatial features.
“Furthermore, the ability of GeAN to learn the temporal interactions embedded in the node and edge features of graphs in their native formats solves the shortcomings associated with using separate feature extraction processes to capture the temporal and spatial features, as is the case in [81,82].”
From TVGeAN: Tensor Visibility Graph-Enhanced Attention Network for Versatile Multivariant Time Series Learning Tasks (2024) · cites this paper as [81]
Cites
Detecting strange attractors in turbulence
Takens, F. (1981) · Lecture Notes in Mathematics · doi:10.1007/bfb0091924 · Cited by 10,459 · see citing works
Deep learning for sensor-based activity recognition: A survey
Wang, J., Chen, Y., Hao, S., Peng, X., & Hu, L. (2019) · Pattern Recognition Letters · doi:10.1016/j.patrec.2018.02.010 · Cited by 2,014 · see citing works
A Bag-of-Features Framework to Classify Time Series
Baydogan, M. G., Runger, G., & Tuv, E. (2013) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2013.72 · Cited by 361 · see citing works
Flagged first, then by citations
Cited by
Sorted by citations
Baz, M. (2024) · Mathematics · doi:10.3390/math12213320 · Cited by 1 · see citing works
- Authors
- Sun, J., Yang, Y., Liu, Y., Chen, C., Rao, W., & Bai, Y.
- Affiliations
- Jiangxi University of Finance and Economics (CN)
- Corresponding author
- Sun, Jiancheng
- Venue
- Pattern Recognition
- Publisher
- Elsevier BV
- Published
- 2019-11
- Volume
- 95
- Pages
- 24-35
- ISSN
- 0031-3203 (ISSN-L)
- OpenAlex
- W2947595568
- Cited by
- 31
- References
- 3
- Citations by year
- 2025: 3 · 2024: 2 · 2023: 5 · 2022: 7 · 2021: 13 · 2020: 1
- FWCI
- 3.32
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Pattern Recognition (publishedVersion)
- Funders
- National Natural Science Foundation of China (61362024, 61662026, 61761020)
- Topics
- Physical Sciences › Computer Science › Signal Processing › Time Series Analysis and Forecasting
- Physical Sciences › Computer Science › Computational Theory and Mathematics › Topological and Geometric Data Analysis
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Image Retrieval and Classification Techniques
- Keywords
- information geometry, covariance matrix features, statistical manifolds, Riemannian manifolds, geodesic distance, tangent space projection, feature fusion, local features, structural networks, functional networks, time series similarity
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
