Preferred Language
Articles
/
hxaB44sBVTCNdQwCquNh
Classification SINGLE-LEAD ECG by using conventional neural network algorithm
...Show More Authors

Scopus Crossref
View Publication
Publication Date
Tue Oct 16 2018
Journal Name
Springer Science And Business Media Llc
MOGSABAT: a metaheuristic hybrid algorithm for solving multi-objective optimisation problems
...Show More Authors

Scopus (68)
Crossref (51)
Scopus Clarivate Crossref
Publication Date
Sat Apr 01 2023
Journal Name
International Journal Of Electrical And Computer Engineering (ijece)
Image encryption algorithm based on the density and 6D logistic map
...Show More Authors

One of the most difficult issues in the history of communication technology is the transmission of secure images. On the internet, photos are used and shared by millions of individuals for both private and business reasons. Utilizing encryption methods to change the original image into an unintelligible or scrambled version is one way to achieve safe image transfer over the network. Cryptographic approaches based on chaotic logistic theory provide several new and promising options for developing secure Image encryption methods. The main aim of this paper is to build a secure system for encrypting gray and color images. The proposed system consists of two stages, the first stage is the encryption process, in which the keys are genera

... Show More
View Publication
Scopus (25)
Crossref (14)
Scopus Crossref
Publication Date
Fri Jun 01 2007
Journal Name
Journal Of Al-nahrain University Science
ON THE GREEDY RADIAL BASIS FUNCTION NEURAL NETWORKS FOR APPROXIMATION MULTIDIMENSIONAL FUNCTIONS
...Show More Authors

The aim of this paper is to approximate multidimensional functions by using the type of Feedforward neural networks (FFNNs) which is called Greedy radial basis function neural networks (GRBFNNs). Also, we introduce a modification to the greedy algorithm which is used to train the greedy radial basis function neural networks. An error bound are introduced in Sobolev space. Finally, a comparison was made between the three algorithms (modified greedy algorithm, Backpropagation algorithm and the result is published in [16]).

View Publication Preview PDF
Crossref (1)
Crossref
Publication Date
Mon Oct 05 2020
Journal Name
International Journal Of Advanced Science And Technology
Improved Merging Multi Convolutional Neural Networks Framework of Image Indexing and Retrieval
...Show More Authors

Improved Merging Multi Convolutional Neural Networks Framework of Image Indexing and Retrieval

Publication Date
Thu Jan 31 2019
Journal Name
Journal Of Engineering
Design of New Hybrid Neural Structure for Modeling and Controlling Nonlinear Systems
...Show More Authors

This paper proposes a new structure of the hybrid neural controller based on the identification model for nonlinear systems. The goal of this work is to employ the structure of the Modified Elman Neural Network (MENN) model into the NARMA-L2 structure instead of Multi-Layer Perceptron (MLP) model in order to construct a new hybrid neural structure that can be used as an identifier model and a nonlinear controller for the SISO linear or nonlinear systems. Weight parameters of the hybrid neural structure with its serial-parallel configuration are adapted by using the Back propagation learning algorithm. The ability of the proposed hybrid neural structure for nonlinear system has achieved a fast learning with minimum number

... Show More
View Publication Preview PDF
Crossref
Publication Date
Fri May 01 2020
Journal Name
International Journal Of Advanced Science And Technology
Improved Merging Multi Convolutional Neural Networks Framework of Image Indexing and Retrieval
...Show More Authors

Background/Objectives: The purpose of current research aims to a modified image representation framework for Content-Based Image Retrieval (CBIR) through gray scale input image, Zernike Moments (ZMs) properties, Local Binary Pattern (LBP), Y Color Space, Slantlet Transform (SLT), and Discrete Wavelet Transform (DWT). Methods/Statistical analysis: This study surveyed and analysed three standard datasets WANG V1.0, WANG V2.0, and Caltech 101. The features an image of objects in this sets that belong to 101 classes-with approximately 40-800 images for every category. The suggested infrastructure within the study seeks to present a description and operationalization of the CBIR system through automated attribute extraction system premised on CN

... Show More
Publication Date
Thu Dec 03 2015
Journal Name
Iraqi Journal Of Science
New multispectral images classification method based on MSR and Skewness implementing on various sensor scenes
...Show More Authors

Publication Date
Mon Oct 03 2022
Journal Name
International Journal Of Nonlinear Analysis And Applications
Use of learning methods for gender and age classification based on front shot face images
...Show More Authors

Publication Date
Tue Jan 01 2013
Journal Name
Ibn Al-haitham Journal For Pure And Applied Science
Classification and Construction of (k,3)-Arcs on Projective Plane Over Galois Field GF(7)
...Show More Authors

The purpose of this work is to study the classification and construction of (k,3)-arcs in the projective plane PG(2,7). We found that there are two (5,3)-arcs, four (6,3)-arcs, six (7,3)arcs, six (8,3)-arcs, seven (9,3)-arcs, six (10,3)-arcs and six (11,3)-arcs. All of these arcs are incomplete. The number of distinct (12,3)-arcs are six, two of them are complete. There are four distinct (13,3)-arcs, two of them are complete and one (14,3)-arc which is incomplete. There exists one complete (15,3)-arc.

Publication Date
Sat Jun 01 2024
Journal Name
Iaes International Journal Of Artificial Intelligence (ij-ai)
A novel fusion-based approach for the classification of packets in wireless body area networks
...Show More Authors

This abstract focuses on the significance of wireless body area networks (WBANs) as a cutting-edge and self-governing technology, which has garnered substantial attention from researchers. The central challenge faced by WBANs revolves around upholding quality of service (QoS) within rapidly evolving sectors like healthcare. The intricate task of managing diverse traffic types with limited resources further compounds this challenge. Particularly in medical WBANs, the prioritization of vital data is crucial to ensure prompt delivery of critical information. Given the stringent requirements of these systems, any data loss or delays are untenable, necessitating the implementation of intelligent algorithms. These algorithms play a pivota

... Show More
View Publication
Scopus Crossref