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ijp-951
An edge detection algorithm matching visual contour perception
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For several applications, it is very important to have an edge detection technique matching human visual contour perception and less sensitive to noise. The edge detection algorithm describes in this paper based on the results obtained by Maximum a posteriori (MAP) and Maximum Entropy (ME) deblurring algorithms. The technique makes a trade-off between sharpening and smoothing the noisy image. One of the advantages of the described algorithm is less sensitive to noise than that given by Marr and Geuen techniques that considered to be the best edge detection algorithms in terms of matching human visual contour perception.

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Publication Date
Tue Jan 08 2019
Journal Name
Iraqi Journal Of Physics
Detection and interpretation of clouds types using visible and infrared satellite images
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One of the most Interesting natural phenomena is clouds that have a very strong effect on the climate, weather and the earth's energy balance. Also clouds consider the key regulator for the average temperature of the plant. In this research monitoring and studying the cloud cover to know the clouds types and whether they are rainy or not rainy using visible and infrared satellite images. In order to interpret and know the types of the clouds visually without using any techniques, by comparing between the brightness and the shape of clouds in the same area for both the visible and infrared satellite images, where the differences in the contrasts of visible image are the albedo differences, while in the infrared images is the temperature d

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Publication Date
Tue Jun 20 2023
Journal Name
Baghdad Science Journal
Detection of Autism Spectrum Disorder Using A 1-Dimensional Convolutional Neural Network
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Autism Spectrum Disorder, also known as ASD, is a neurodevelopmental disease that impairs speech, social interaction, and behavior. Machine learning is a field of artificial intelligence that focuses on creating algorithms that can learn patterns and make ASD classification based on input data. The results of using machine learning algorithms to categorize ASD have been inconsistent. More research is needed to improve the accuracy of the classification of ASD. To address this, deep learning such as 1D CNN has been proposed as an alternative for the classification of ASD detection. The proposed techniques are evaluated on publicly available three different ASD datasets (children, Adults, and adolescents). Results strongly suggest that 1D

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Publication Date
Wed May 10 2023
Journal Name
Diagnostics
A Deep Feature Fusion of Improved Suspected Keratoconus Detection with Deep Learning
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Detection of early clinical keratoconus (KCN) is a challenging task, even for expert clinicians. In this study, we propose a deep learning (DL) model to address this challenge. We first used Xception and InceptionResNetV2 DL architectures to extract features from three different corneal maps collected from 1371 eyes examined in an eye clinic in Egypt. We then fused features using Xception and InceptionResNetV2 to detect subclinical forms of KCN more accurately and robustly. We obtained an area under the receiver operating characteristic curves (AUC) of 0.99 and an accuracy range of 97–100% to distinguish normal eyes from eyes with subclinical and established KCN. We further validated the model based on an independent dataset with

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Publication Date
Wed Jan 01 2020
Journal Name
International Journal Of Computational Intelligence Systems
Evolutionary Feature Optimization for Plant Leaf Disease Detection by Deep Neural Networks
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Publication Date
Fri Jan 01 2021
Journal Name
Ieee Access
Fast Shot Boundary Detection Based on Separable Moments and Support Vector Machine
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Publication Date
Wed Jun 16 2021
Journal Name
Cognitive Computation
Deep Transfer Learning for Improved Detection of Keratoconus using Corneal Topographic Maps
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Abstract <p>Clinical keratoconus (KCN) detection is a challenging and time-consuming task. In the diagnosis process, ophthalmologists must revise demographic and clinical ophthalmic examinations. The latter include slit-lamb, corneal topographic maps, and Pentacam indices (PI). We propose an Ensemble of Deep Transfer Learning (EDTL) based on corneal topographic maps. We consider four pretrained networks, SqueezeNet (SqN), AlexNet (AN), ShuffleNet (SfN), and MobileNet-v2 (MN), and fine-tune them on a dataset of KCN and normal cases, each including four topographic maps. We also consider a PI classifier. Then, our EDTL method combines the output probabilities of each of the five classifiers to obtain a decision b</p> ... Show More
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Publication Date
Tue Dec 15 2020
Journal Name
Al-academy
Simulation As One Of The Tools Of Visual Thinking And Its Effect On Developing Drawing And Design Skills To Produce Innovative Artworks: عائشة عبد الجبار العيسى
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The research emphasizes importance of preliminary drawings in design of any product. Therefore, using of simulation as tools for visual thinking in developing drawing and design skills. So that practice of drawing by hand, considering shape of ideas in first stage of visualizations, and practice of its techniques and continuous training.
Hence, the research problem arose with the role of simulation method for developing preliminary sketches in the sample of students of the Product Design Department at the College of Design and Art, PNU, as it is important tool for visual thinking that helps the designer in designing and producing innovative artistic works.
Therefore, the research axes, a number of findings and recommendations were

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Publication Date
Tue Mar 01 2016
Journal Name
Al-academy
The effectiveness of visual intelligence strategy in the collection of students in the Department of Art Education in the perspective material: أسامة حسن عبد علي الصفار
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Select the researcher discussed problem of asking the following : Do you use visual intelligence strategy effective in the collection of students in the Department of Art Education in the foreseeable material ? The research aims to " measure the effectiveness of the strategy in the collection of visual intelligence students in the Department of Art Education in the foreseeable material ". To verify the objective of this research was identify hypotheses zero to measure the level of achievement in the foreseeable material second grade students in the Department of Art Education - Faculty of Fine Arts . The population of the research students in the Department of Art Education / Faculty of Fine Arts at the University of Baghdad who are stud

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Publication Date
Sun May 01 2022
Journal Name
International Journal Of Early Childhood Special Education (int-jecs)
Study of some visual functions and functional variables of the respiratory and nervous systems and their relationship to the level of achievement of air rifle shooting
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The purpose of this paper is to identifying the relationship between some visual functions and the level of achievement of air rifle shooting among young Iraqi female, and identifying the relationship between some functional variables of the respiratory and nervous systems at the level of achievement of air rifle shooting among young Iraqi female. The researchers used the descriptive approach in the correlative relationships style for its suitability and the research problem. The researchers determined the research community by the intentional method represented by (10) young female shooters who represent the national team with air rifle shooting effectiveness, and who represent (100%) of the research community. One of the most important re

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Publication Date
Tue Mar 01 2022
Journal Name
International Journal Of Nonlinear Analysis And Applications
Semi-parametric regression function estimation for environmental pollution with measurement error using artificial flower pollination algorithm
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Artificial Intelligence Algorithms have been used in recent years in many scientific fields. We suggest employing flower pollination algorithm in the environmental field to find the best estimate of the semi-parametric regression function with measurement errors in the explanatory variables and the dependent variable, where measurement errors appear frequently in fields such as chemistry, biological sciences, medicine, and epidemiological studies, rather than an exact measurement. We estimate the regression function of the semi-parametric model by estimating the parametric model and estimating the non-parametric model, the parametric model is estimated by using an instrumental variables method (Wald method, Bartlett’s method, and Durbin

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