Multimodal approach to feature extraction for image and signal learning problems

Damian R. Eads; Steven J. Williams; James Theiler; Reid Porter; Neal R. Harvey; Simon J. Perkins; Steven P. Brumby; Nancy A. David

doi:10.1117/12.506611

30 December 2003 Multimodal approach to feature extraction for image and signal learning problems

Damian R. Eads, Steven J. Williams, James Theiler, Reid Porter, Neal R. Harvey, Simon J. Perkins, Steven P. Brumby, Nancy A. David

Author Affiliations +

Proceedings Volume 5200, Applications and Science of Neural Networks, Fuzzy Systems, and Evolutionary Computation VI; (2003) https://doi.org/10.1117/12.506611
Event: Optical Science and Technology, SPIE's 48th Annual Meeting, 2003, San Diego, California, United States

Abstract

We present ZEUS, an algorithm for extracting features from images and time series signals. ZEIS is designed to solve a variety of machine learning problems including time series forecasting, signal classification, image and pixel classification of multispectral and panchromatic imagery. An evolutionary approach is used to extract features from a near-infinite space of possible combinations of nonlinear operators. Each problem type (i.e. signal or image, regression or classification, multiclass or binary) has its own set of primitive operators. We employ fairly generic operators, but note that the choice of which operators to use provides an opportunity to consult with a domain expert. Each feature is produced from a composition of some subset of these primitive operators. The fitness for an evolved set of features is given by the performance of a back-end classifier (or regressor) on training data. We demonstrate our multimodal approach to feature extraction on a variety of problems in remote sensing. The performance of this algorithm will be compared to standard approaches, and the relative benefit of various aspects of the algorithm will be investigated.

Citation Download Citation

Damian R. Eads, Steven J. Williams, James Theiler, Reid Porter, Neal R. Harvey, Simon J. Perkins, Steven P. Brumby, and Nancy A. David "Multimodal approach to feature extraction for image and signal learning problems", Proc. SPIE 5200, Applications and Science of Neural Networks, Fuzzy Systems, and Evolutionary Computation VI, (30 December 2003); https://doi.org/10.1117/12.506611

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available