Cited by 2,504Advanced Neural Network ApplicationsAdvanced Image and Video Retrieval TechniquesDomain Adaptation and Few-Shot Learning

Deep learning for visual understanding: A review

Open access
Guo, Yanming, Liu, Yu, Oerlemans, Ard, Lao, Songyang, Wu, Song, Lew, Michael S.·2016·Neurocomputing

Integrity signals

Registry

Crossref · 10.1016/j.neucom.2015.09.116

Cites

210 of 210 references verified0 citation errors · 0 not checkable

Statistics

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

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Cites

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Authors
Guo, Y., Liu, Y., Oerlemans, A., Lao, S., Wu, S., & Lew, M. S.
Affiliations
  • Leiden University (NL)
  • National University of Defense Technology (CN)
Corresponding author
Lew, Michael S.
Venue
Neurocomputing
Publisher
Elsevier BV
Published
2016-04
Volume
187
Pages
27-48
ISSN
0925-2312 (ISSN-L)
OpenAlex
W2176950688
Cited by
2,504
References
210
Citations by year
2026: 111 · 2025: 236 · 2024: 284 · 2023: 305 · 2022: 335 · 2021: 350 · 2020: 343 · 2019: 239 · 2018: 182 · 2017: 90 · 2016: 27 · 2012: 1
FWCI
86.55
Type
journal article
Language
en
Locations
  • Neurocomputing (publishedVersion)
  • Leiden Repository (Leiden University) (submittedVersion)
  • Data Archiving and Networked Services (DANS) (submittedVersion)
Funders
  • Leiden University (2006002026)
  • National University of Defense Technology (61571453)
  • NWO (642.066.603)
  • NVIDIA Corporation (NV72915)
Topics
  • Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Advanced Neural Network Applications
  • Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Advanced Image and Video Retrieval Techniques
  • Physical Sciences › Computer Science › Artificial Intelligence › Domain Adaptation and Few-Shot Learning
Keywords
deep learning, computer vision, visual understanding, image classification, object detection, image retrieval, semantic segmentation, human pose estimation, distributed representations, deep neural network training

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.

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