Paper Info
Title
Incorporating Domain High-Level Concepts into Heuristic Searches: A Case Study on Identifying Plant Species in Remote Sensing Images
Abstract
In order to take domain expert knowledge as a supplement of the machine "intelLigence", a High-Level-Concept-based framework (HLC) for heuristic search is proposed. HLC has domain experts actively generaLize their own psychological feeLings about image features into high-level concepts, then write down them in descriptors, and make the domain high-level concepts enter a heuristic search with a multi-descriptor combination. These so-called "descriptors" are a kind of non-threshold models so that they have reusabiLity and generaLization. To demonstrate the idea, 18 new descriptor have been designed. The examinations of discrimination accuracy indicate that in a multi-descriptor space, the error rates of classification is 67.91% lower than that in a spectral-brightness space.
Year
DOI
Venue
2011
10.1109/ICDMA.2011.157
ICDMA
Keywords
Field
DocType
expert systems,geophysical image processing,image classification,knowledge engineering,remote sensing,vegetation,descriptors,domain expert knowledge,domain high level concepts,heuristic searches,high level concept based framework,nonthreshold models,plant species identification,remote sensing images,spectral-brightness space,descriptors,domain high-level concepts,machine discrimination,plant species
Heuristic,Feature (computer vision),Computer science,Subject-matter expert,Expert system,Artificial intelligence,Knowledge engineering,Contextual image classification,Reusability,Machine learning,Plant species
Conference
Citations 
PageRank 
References 
0
0.34
5
Authors
2
Name
Order
Citations
PageRank
J. H. Zhou1241.62
Y. F. Zhou200.34