Use of learning methods for gender and age classification based on front shot face images
Publication Date
Fri Jan 07 2022
Journal Name
International Journal Of Early Childhood Special Education
Hierarchical learning and its effect on learning some basic skills in fencing for third stage students.
MH Hamzah, AF Abbas, International Journal of Early Childhood Special Education, 2022
Publication Date
Tue Jan 01 2019
Journal Name
J. Mech. Cont.& Math. Scis
Publication Date
Tue Oct 01 2024
Journal Name
Separation And Purification Technology
A comprehensive review on the use of Ti3C2Tx MXene in membrane-based water treatment
2D materials
Membrane-based processes
MXenes
Ti3C2Tx
Water treatment
(17)
(16)
Publication Date
Sat Dec 01 2012
Journal Name
Journal Of Engineering
Effect Of Technology Based Learning As A Supplement To Traditional Technology On Student's Achievement
e-learning
m-learning
voting system
automated examination
smart board
bluetooth broadcasting system
This paper describes a practical study on the impact of learning's partners, Bluetooth Broadcasting system, interactive board, Real – time response system, notepad, free internet access, computer based examination, and interaction classroom, etc, had on undergraduate student performance, achievement and involving with lectures. The goal of this study is to test the hypothesis that the use of such learning techniques, tools, and strategies to improve student learning especially among the poorest performing students. Also, it gives some kind of practical comparison between the traditional way and interactive way of learning in terms of lectures time, number of tests, types of tests, student's scores, and student's involving with lectures
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Publication Date
Wed May 10 2017
Journal Name
Australian Journal Of Basic And Applied Sciences
Publication Date
Thu Nov 03 2022
Journal Name
Sensors
A Novel Application of Deep Learning (Convolutional Neural Network) for Traumatic Spinal Cord Injury Classification Using Automatically Learned Features of EMG Signal
In this study, a traumatic spinal cord injury (TSCI) classification system is proposed using a convolutional neural network (CNN) technique with automatically learned features from electromyography (EMG) signals for a non-human primate (NHP) model. A comparison between the proposed classification system and a classical classification method (k-nearest neighbors, kNN) is also presented. Developing such an NHP model with a suitable assessment tool (i.e., classifier) is a crucial step in detecting the effect of TSCI using EMG, which is expected to be essential in the evaluation of the efficacy of new TSCI treatments. Intramuscular EMG data were collected from an agonist/antagonist tail muscle pair for the pre- and post-spinal cord lesi
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(9)
(9)
Publication Date
Sat Feb 02 2019
Journal Name
Journal Of The College Of Education For Women
Publication Date
Wed Mar 01 2017
Journal Name
Un Published
Publication Date
Tue Aug 10 2021
Journal Name
Design Engineering
Lossy Image Compression Using Hybrid Deep Learning Autoencoder Based On kmean Clusteri
Image compression
Convolutional Autoencoder (CAE)
k-mean algorithm
PSNR
Compression Rate (CR)
MSE
Clustering
CLIC
Kodak
deep learning
lossy
Image compression plays an important role in reducing the size and storage of data while increasing the speed of its transmission through the Internet significantly. Image compression is an important research topic for several decades and recently, with the great successes achieved by deep learning in many areas of image processing, especially image compression, and its use is increasing Gradually in the field of image compression. The deep learning neural network has also achieved great success in the field of processing and compressing various images of different sizes. In this paper, we present a structure for image compression based on the use of a Convolutional AutoEncoder (CAE) for deep learning, inspired by the diversity of human eye
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Sun Feb 10 2019
Journal Name
Iraqi Journal Of Physics
A nonlinear edge –preserving smoothing filter for edge detection on color and gray satellite images
Edge detection
nonlinear filters
Gaussian noise
Sobel operator
color image.
A nonlinear filter for smoothing color and gray images
corrupted by Gaussian noise is presented in this paper. The proposed
filter designed to reduce the noise in the R,G, and B bands of the
color images and preserving the edges. This filter applied in order to
prepare images for further processing such as edge detection and
image segmentation.
The results of computer simulations show that the proposed
filter gave satisfactory results when compared with the results of
conventional filters such as Gaussian low pass filter and median filter
by using Cross Correlation Coefficient (ccc) criteria.