Entropy-Based and Weighted Selective SIFT Clustering as an Energy Aware Framework for Supervised Visual Recognition of Man-Made Structures
Using local invariant features has been proven by published literature to be powerful for image processing and pattern recognition tasks. However, in energy aware environments, these invariant features would not scale easily because of their computational requirements. Motivated to find an efficien...
Main Authors: | Ayman El Mobacher, Nicholas Mitri, Mariette Awad |
---|---|
Format: | Article |
Language: | English |
Published: |
Hindawi Limited
2013-01-01
|
Series: | Mathematical Problems in Engineering |
Online Access: | http://dx.doi.org/10.1155/2013/730143 |
Similar Items
-
Deep belief networks and cortical algorithms: A comparative study for supervised classification
by: Yara Rizk, et al.
Published: (2019-07-01) -
Face Recognition Using SIFT and PCA
by: Tzu-Yen Shu, et al.
Published: (2008) -
Hand Gesture Recognition Using Adaboost with SIFT
by: Ko-Chih Wang, et al. -
The study of hand gesture recognition based on SIFT
by: Cheng-Huan Hsieh, et al.
Published: (2015) -
Currency recognition using a smartphone: Comparison between color SIFT and gray scale SIFT algorithms
by: Iyad Abu Doush, et al.
Published: (2017-10-01)