Co-Authors:
Laykin, S., Dept. of Industrial Engineering, Ben- Gurion University of the Negev, Beer-Sheva 84105, Israel
Edan, Y., Dept. of Industrial Engineering, Ben- Gurion University of the Negev, Beer-Sheva 84105, Israel
Alchanatis, V., Inst. of Agricultural Engineering, ARO, Volcani Center, Bet- Dagan 50250, Israel
Abstract:
This paper presents an on-line hierarchical classifier for agricultural products. The classifier consists of two levels. The first level detects new populations using an on-line clustering algorithm. The second level selects the best-fit classifier using a fuzzy system. This paper presents the combination of the two levels into a complete system. Feature selection is conducted on-line according to the classified population. A synthetic dataset is used to estimate the classifier capabilities and compare it to previous results. Results indicated that the combined online system results in improved classification accuracy.
תפריט נגישות
ניגודיות עדינה
מונוכרום
הדגשת קישורים
חסימת אנימציה
פונט קריא
סגור
איפוס הגדרות נגישות
להורדת מודול נגישות חינם
