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A Trainable System for Object Detection
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At early times of object detection, NMS was not always integrated.
“At early times of object detection, NMS was not always integrated [121].”
From Object Detection in 20 Years: A Survey (2023) · cites this paper as [121]
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Metadata
- Authors
- Papageorgiou, C., & Poggio, T.
- Affiliations
- Massachusetts Institute of Technology (US)
- ORCID
- Poggio, Tomaso
- Venue
- International Journal of Computer Vision
- Published
- 2000-06
- Volume
- 38
- Issue
- 1
- Pages
- 15-33
- ISSN
- 0920-5691 (ISSN-L)
- 1573-1405
- OpenAlex
- W1608462934
- Cited by
- 1,289
- References
- 36
- Citations by year
- 2026: 6 · 2025: 24 · 2024: 24 · 2023: 36 · 2022: 39 · 2021: 56 · 2020: 27 · 2019: 37 · 2018: 47 · 2017: 55 · 2016: 57 · 2015: 78 · 2014: 98 · 2013: 97 · 2012: 88
- FWCI
- 22.67
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- Locations
- International Journal of Computer Vision (publishedVersion)
- Funders
- National Science Foundation
- Massachusetts Institute of Technology
- 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 › Computer Vision and Pattern Recognition › Video Surveillance and Tracking Methods
- Keywords
- object detection, Haar wavelet transform, overcomplete dictionary, support vector machine, learning from examples, face detection, human detection, car detection, driver assistance systems, real-time detection, cluttered scenes
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