@article{ref1,
title="Adaptive hierarchical architecture for visual recognition",
journal="Applied optics",
year="2010",
author="Tivive, Fok H. C. and Bouzerdoum, Abdesselam and Phung, Son Lam and Iftekharuddin, Khan M.",
volume="49",
number="10",
pages="B1-8",
abstract="We propose a new hierarchical architecture for visual pattern classification. The new architecture consists of a set of fixed, directional filters and a set of adaptive filters arranged in a cascade structure. The fixed filters are used to extract primitive features such as orientations and edges that are present in a wide range of objects, whereas the adaptive filters can be trained to find complex features that are specific to a given object. Both types of filter are based on the biological mechanism of shunting inhibition. The proposed architecture is applied to two problems: pedestrian detection and car detection. Evaluation results on benchmark data sets demonstrate that the proposed architecture outperforms several existing ones.<p /> <p>Language: en</p>",
language="en",
issn="0003-6935",
doi="",
url="http://dx.doi.org/"
}