Cited by 53Hand Gesture Recognition SystemsContext-Aware Activity Recognition SystemsHuman Pose and Action Recognition

Multimodal Gesture Recognition Using Multi-stream Recurrent Neural Network

Nishida, Noriki, Nakayama, Hideki·2016·Lecture Notes in Computer Science

Integrity signals

Registry

Crossref · 10.1007/978-3-319-29451-3_54

Cites

33 of 33 references verified0 citation errors · 0 not checkable

Statistics

Recomputing p-values needs the paper’s full text.

Claims the paper makes

We couldn’t retrieve this paper’s full text, so its claims and self-check weren’t run. The registry and citation checks still apply.

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?

Cites

Flagged first, then by citations

2 of the 35 references couldn’t be matched to a known paper.

Cited by

Sorted by citations

Authors
Nishida, N., & Nakayama, H.
Affiliations
The University of Tokyo (JP)
Corresponding author
Nishida, Noriki
Venue
Lecture Notes in Computer Science
Published
2016
Pages
682-694
ISSN
  • 0302-9743 (ISSN-L)
  • 1611-3349
OpenAlex
W2405546895
Cited by
53
References
35
Citations by year
2025: 2 · 2024: 1 · 2023: 2 · 2022: 4 · 2021: 9 · 2020: 3 · 2019: 10 · 2018: 11 · 2017: 7 · 2016: 4
FWCI
7.28
Type
conference paper
Language
en
Open access
closed
Locations
Lecture notes in computer science (publishedVersion)
Funders
Japan Society for the Promotion of Science (26730085)
Topics
  • Physical Sciences › Computer Science › Human-Computer Interaction › Hand Gesture Recognition Systems
  • Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Context-Aware Activity Recognition Systems
  • Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Human Pose and Action Recognition
Keywords
multimodal gesture recognition, LSTM, end-to-end learning, Kinect sensor, noise robustness

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