Name
Title | ||
|---|---|---|
Model and feature selection for the classification of dark field pollen images using the classifynder system |
Abstract | ||
|---|---|---|
This paper explores the use of SURF features and local binary patterns, for the classification of extended depth of focus, dark field, pollen images. The paper outlines the image collection method, feature extraction process, and also compares the performance of a number of different classifiers across a range of data sets. |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1109/IVCNZ.2017.8402498 | 2017 International Conference on Image and Vision Computing New Zealand (IVCNZ) |
Keywords | Field | DocType |
Palynology,Computer Vision,Image Classification,Bag of Visual Words1 | Depth of focus,Computer vision,Data set,Pattern recognition,Feature selection,Computer science,Visualization,Local binary patterns,Pollen,Dark field microscopy,Feature extraction,Artificial intelligence | Conference |
ISSN | ISBN | Citations |
2151-2191 | 978-1-5386-4277-1 | 0 |
PageRank | References | Authors |
0.34 | 6 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ben Pedersen | 1 | 0 | 0.34 |
| D. G. Bailey | 2 | 71 | 16.88 |
| Robert M. Hodgson | 3 | 37 | 18.37 |
| Katherine Holt | 4 | 0 | 0.34 |
| Stephen Marsland | 5 | 14 | 6.33 |