50 Years of object recognition: Directions forward
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Claims the paper makes
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Each is checked against this paper’s own text: does it say what the citing paper says it does?
The research reviewed in Grauman and Leibe (2011), Andreopoulos and Tsotsos (2013) and Zhang et al. (2013) is mostly pre-2012, prior to the recent success and dominance of deep learning.
“However, the research reviewed in Grauman and Leibe (2011), Andreopoulos and Tsotsos (2013) and Zhang et al. (2013) is mostly pre-2012, and therefore prior to the recent striking success and dominance of deep learning and related methods.”
From Deep Learning for Generic Object Detection: A Survey (2020) · cites this paper as Andreopoulos and Tsotsos 2013
Terms such as detection, localization, recognition, classification, categorization, verification, identification, annotation, labeling, and understanding are often differently defined.
“Terms such as detection, localization, recognition, classification, categorization, verification, identification, annotation, labeling, and understanding are often differently defined(Andreopoulos and Tsotsos 2013).”
From Deep Learning for Generic Object Detection: A Survey (2020) · cites this paper as Andreopoulos and Tsotsos 2013
There is no universal agreement in the literature on the definitions of various vision subtasks.
“To the best of our knowledge, there is no universal agreement in the literature on the definitions of various vision subtasks.”
From Deep Learning for Generic Object Detection: A Survey (2020) · cites this paper as Andreopoulos and Tsotsos 2013
The citation lists haven’t been fetched yet
References 385 · Cited by 347
- Authors
- Andreopoulos, A., & Tsotsos, J. K.
- Affiliations
- IBM Research - Almaden (US)
- York University (CA)
- Corresponding author
- Andreopoulos, Alexander
- Venue
- Computer Vision and Image Understanding
- Publisher
- Elsevier BV
- Published
- 2013-08
- Volume
- 117
- Issue
- 8
- Pages
- 827-891
- ISSN
- 1077-3142 (ISSN-L)
- OpenAlex
- W2067381981
- Cited by
- 347
- References
- 385
- Citations by year
- 2026: 3 · 2025: 11 · 2024: 13 · 2023: 13 · 2022: 16 · 2021: 29 · 2020: 62 · 2019: 32 · 2018: 42 · 2017: 35 · 2016: 34 · 2015: 34 · 2014: 21 · 2013: 2
- FWCI
- 34.11
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- Locations
- Computer Vision and Image Understanding (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Advanced Image and Video Retrieval Techniques
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Advanced Neural Network Applications
- Physical Sciences › Computer Science › Artificial Intelligence › Domain Adaptation and Few-Shot Learning
- Keywords
- object recognition, optical character recognition, industrial inspection, diagnostic imaging, biometrics, semantic gap, object representation, generalization
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.
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