A study regarding the generalization capacity of image classification by using neuroal networks in Matlab

Author

al-Rabii, Evan Madi Hamzah

Source

Journal of Babylon University : Journal of Applied and Pure Sciences

Issue

Vol. 26, Issue 4 (30 Apr. 2018), pp.45-56, 12 p.

Publisher

University of Babylon

Publication Date

2018-04-30

Country of Publication

Iraq

No. of Pages

12

Main Subjects

Engineering & Technology Sciences (Multidisciplinary)

Abstract EN

The paper performs an algorithmic and experimental study regarding the generalization capacity of the scheme based on neuronal networks for the recognition of new images of the face.

This enables both a rendering of graphic representations and the classification of image classes in Matlab.

The purpose is to describe the recognition algorithm, to project and implement an application which proposes both the graphic representation of the images used by the neuronal training algorithm but also the implementation of the perceptron neuronal algorithm and the determination of the generalization capacity of the separating hyper plane of the considered image classes.

American Psychological Association (APA)

al-Rabii, Evan Madi Hamzah. 2018. A study regarding the generalization capacity of image classification by using neuroal networks in Matlab. Journal of Babylon University : Journal of Applied and Pure Sciences،Vol. 26, no. 4, pp.45-56.
https://search.emarefa.net/detail/BIM-1093482

Modern Language Association (MLA)

al-Rabii, Evan Madi Hamzah. A study regarding the generalization capacity of image classification by using neuroal networks in Matlab. Journal of Babylon University : Journal of Applied and Pure Sciences Vol. 26, no. 4 (2018), pp.45-56.
https://search.emarefa.net/detail/BIM-1093482

American Medical Association (AMA)

al-Rabii, Evan Madi Hamzah. A study regarding the generalization capacity of image classification by using neuroal networks in Matlab. Journal of Babylon University : Journal of Applied and Pure Sciences. 2018. Vol. 26, no. 4, pp.45-56.
https://search.emarefa.net/detail/BIM-1093482

Data Type

Journal Articles

Language

English

Notes

Record ID

BIM-1093482