R
Reid B. Porter
Researcher at Los Alamos National Laboratory
Publications - 66
Citations - 2821
Reid B. Porter is an academic researcher from Los Alamos National Laboratory. The author has contributed to research in topics: Image processing & Feature extraction. The author has an hindex of 18, co-authored 66 publications receiving 2570 citations. Previous affiliations of Reid B. Porter include Queensland University of Technology & University of Cambridge.
Papers
More filters
Journal ArticleDOI
Faster and Better: A Machine Learning Approach to Corner Detection
TL;DR: A new heuristic for feature detection is presented and, using machine learning, a feature detector is derived from this which can fully process live PAL video using less than 5 percent of the available processing time.
Journal ArticleDOI
Comparison of GENIE and conventional supervised classifiers for multispectral image feature extraction
Neal R. Harvey,James Theiler,Steven P. Brumby,Simon Perkins,John J. Szymanski,Jeffrey J. Bloch,Reid B. Porter,M. Galassi,Aaron Cody Young +8 more
TL;DR: The authors describe their system in detail together with experiments involving comparisons of GENIE with several conventional supervised classification techniques, for a number of classification tasks using multispectral remotely sensed imagery.
Proceedings ArticleDOI
Genetic algorithms and support vector machines for time series classification
TL;DR: This work introduces an algorithm for classifying time series data that employs evolutionary computation for feature extraction, and a support vector machine for the final backend classification.
Journal ArticleDOI
Wide-Area Motion Imagery
TL;DR: Advances that have been made and the advances that will be needed to produce the hierarchy of computational models required to narrow the semantic gap in WAMI are described.
Proceedings ArticleDOI
GENIE: a hybrid genetic algorithm for feature classification in multispectral images
Simon Perkins,James Theiler,Steven P. Brumby,Neal R. Harvey,Reid B. Porter,John J. Szymanski,Jeffrey J. Bloch +6 more
TL;DR: Genie as mentioned in this paper is a hybrid learning system that combines a GA and a more conventional classifier to output a final classification. But the GA alone is not sufficient to correctly classify a pixel.