Fusion of global shape and local features using meta-classifier framework.
In computer vision, objects in an image can be described using many features such as shape, color, texture and local features. The number of dimensions for each type of feature has differing size. Basically, the underlying belief from a recognition point of view is that, the more features being used...
Main Authors: | Manshor, Noridayu, Abdul Rahiman, Amir Rizaan, Raja Mahmood, Raja Azlina |
---|---|
Format: | Article |
Language: | English English |
Published: |
Praise Worthy Prize
2013
|
Online Access: | http://psasir.upm.edu.my/id/eprint/30671/1/Fusion%20of%20global%20shape%20and%20local%20features%20using%20meta.pdf |
Similar Items
-
Meta-classifier based on boosted approach for object class recognition
by: Manshor, Noridayu, et al.
Published: (2014) -
Fusion Of Global Shape And Local Features Using Multi Classifier Framework For Object Class Recognition
by: Manshor, Noridayu
Published: (2013) -
Performance evaluation of intrusion detection system using selected features and machine learning classifiers
by: Raja Mahmood, Raja Azlina, et al.
Published: (2021) -
Feature detector-level fusion methods in food recognition
by: Razali @ Ghazali, Mohd Norhisham, et al.
Published: (2019) -
IoT based poultry house monitoring
by: Manshor, Noridayu, et al.
Published: (2019)