The DOI matches its Crossref record; 8 of the 8 references it cites were found in a registry or an index.
Object Recognition with Features Inspired by Visual Cortex
Abstract
We introduce a novel set of features for robust object recognition. Each element of this set is a complex feature obtained by combining position- and scale-tolerant edge-detectors over neighboring positions and multiple orientations. Our system's architecture is motivated by a quantitative model of visual cortex. We show that our approach exhibits excellent recognition performance and outperforms several state-of-the-art systems on a variety of image datasets including many different object categories. We also demonstrate that our system is able to learn from very few examples. The performance of the approach constitutes a suggestive plausibility proof for a class of feedforward models of object recognition in cortex.
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Cites
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What is the best multi-stage architecture for object recognition?
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Facial Expression Recognition Using Facial Movement Features
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(2010) · Cited by 94
Metadata
- Authors
- Serre, T., Wolf, L., & Poggio, T.
- Venue
- 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05)
- Publisher
- IEEE
- Published
- 2005-07-27
- Volume
- 2
- Pages
- 994-1000
- ISSN
- 1063-6919 (ISSN-L)
- OpenAlex
- W1624854622
- Cited by
- 821
- References
- 8
- FWCI
- 34.65
- Type
- conference paper
- Language
- en
- Open access
- closed
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