In this work, we suggest a new feature selection technique that lets us use the wrapper approach for finding a well suited feature set for distinguishing experiment classes in hig...
This paper describes an object detection framework that learns the discriminative co-occurrence of multiple features. Feature co-occurrences are automatically found by Sequential F...
This paper presents a generic features selection method and its applications on some document analysis problems. The method is based on a genetic algorithm (GA), whose tness funct...
This paper deals with robust point features selection for tracking. The aim is to identify unreliable features since the first frame so to track them in all the sequence. We exten...
The purpose of this research is to develop effective machine learning or data mining techniques based on flexible neural tree FNT. Based on the pre-defined instruction/operator se...