Author
CATALTEPE, ZEHRA - SIEMENS CORP | |
Pearson, Thomas | |
CETIN, ENIS - BILKENT UNIV, TURKEY |
Submitted to: Meeting Proceedings
Publication Type: Research Notes Publication Acceptance Date: 5/14/2004 Publication Date: N/A Citation: N/A Interpretive Summary: Technical Abstract: We used transmittance images and different learning algorithms to classify insect damaged and un-damaged wheat kernels. Using the histogram of the pixels of the wheat images as the feature, and the linear model as the learning algorithm, we achieved a False Positive Rate (1-specificity) of 0.12 at the True Positive Rate (sensitivity) of 0.8 and an Area Under the ROC Curve (AUC) of 0.90 ± 0.02. Combining the linear model and a Radial Basis Function Network in a committee resulted in a FP Rate of 0.09 at the TP Rate of 0.8 and an AUC of 0.93 ± 0.03. |