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Face-based Gender Classification Using Deep Learning Model
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Gender classification is a critical task in computer vision. This task holds substantial importance in various domains, including surveillance, marketing, and human-computer interaction. In this work, the face gender classification model proposed consists of three main phases: the first phase involves applying the Viola-Jones algorithm to detect facial images, which includes four steps: 1) Haar-like features, 2) Integral Image, 3) Adaboost Learning, and 4) Cascade Classifier. In the second phase, four pre-processing operations are employed, namely cropping, resizing, converting the image from(RGB) Color Space to (LAB) color space, and enhancing the images using (HE, CLAHE). The final phase involves utilizing Transfer learning, a powerful deep learning technique that can be effectively employed to Face gender classification using the Alex-Net architecture. The performance evaluation of the proposed gender classification model encompassed three datasets: the LFW dataset, which contained 1,200 facial images. The Faces94 dataset contained 400 facial images, and the family dataset had 400. The Transfer Learning with the Alex-Net model achieved an accuracy of 98.77% on the LFW dataset.

Furthermore, the model attained an accuracy rate of 100% on both the Faces94 and family datasets. Thus, the proposed system emphasizes the significance of employing pre-processing techniques and transfer learning with the Alex-Net model. These methods contribute to more accurate results in gender classification. Where, the results achieved by applying image contrast enhancement techniques, such as HE and CLAHE, were compared. CLAHE achieved the best facial classification accuracy compared to HE.

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Publication Date
Fri Aug 13 2021
Journal Name
Neural Computing And Applications
Integration of extreme gradient boosting feature selection approach with machine learning models: application of weather relative humidity prediction
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Publication Date
Fri Feb 21 2025
Journal Name
2025 First International Conference On Advances In Computer Science, Electrical, Electronics, And Communication Technologies (ce2ct)
Enhancing Cloud Security Implementing AI-Based Intrusion Detection Systems
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The increasing complexity of assaults necessitates the use of innovative intrusion detection systems (IDS) to safeguard critical assets and data. There is a higher risk of cyberattacks like data breaches and unauthorised access since cloud services have been used more frequently. The project's goal is to find out how Artificial Intelligence (AI) could enhance the IDS's ability to identify and classify network traffic and identify anomalous activities. Online dangers could be identified with IDS. An intrusion detection system, or IDS, is required to keep networks secure. We must create efficient IDS for the cloud platform as well, since it is constantly growing and permeating more aspects of our daily life. However, using standard intrusion

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Publication Date
Tue Feb 01 2011
Journal Name
Iop Conference Series: Materials Science And Engineering
Contour extraction of echocardiographic images based on pre-processing
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In this work we present a technique to extract the heart contours from noisy echocardiograph images. Our technique is based on improving the image before applying contours detection to reduce heavy noise and get better image quality. To perform that, we combine many pre-processing techniques (filtering, morphological operations, and contrast adjustment) to avoid unclear edges and enhance low contrast of echocardiograph images, after implementing these techniques we can get legible detection for heart boundaries and valves movement by traditional edge detection methods.

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Publication Date
Mon Jul 01 2019
Journal Name
Arpn Journal Of Engineering And Applied Sciences
PSEUDO RANDOM NUMBER GENERATOR BASED ON NEURO-FUZZY MODELS
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Producing pseudo-random numbers (PRN) with high performance is one of the important issues that attract many researchers today. This paper suggests pseudo-random number generator models that integrate Hopfield Neural Network (HNN) with fuzzy logic system to improve the randomness of the Hopfield Pseudo-random generator. The fuzzy logic system has been introduced to control the update of HNN parameters. The proposed model is compared with three state-ofthe-art baselines the results analysis using National Institute of Standards and Technology (NIST) statistical test and ENT test shows that the projected model is statistically significant in comparison to the baselines and this demonstrates the competency of neuro-fuzzy based model to produce

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Publication Date
Sun Jun 01 2014
Journal Name
Baghdad Science Journal
Multifocus Images Fusion Based On Homogenity and Edges Measures
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Image fusion is one of the most important techniques in digital image processing, includes the development of software to make the integration of multiple sets of data for the same location; It is one of the new fields adopted in solve the problems of the digital image, and produce high-quality images contains on more information for the purposes of interpretation, classification, segmentation and compression, etc. In this research, there is a solution of problems faced by different digital images such as multi focus images through a simulation process using the camera to the work of the fuse of various digital images based on previously adopted fusion techniques such as arithmetic techniques (BT, CNT and MLT), statistical techniques (LMM,

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Publication Date
Wed Mar 20 2019
Journal Name
Journal Of Legal Sciences
Sale Based on an Open Price – A Comparative Study
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The ultimate goal of any sale contract is to maximize the combined returns of the parties, knowing that these returns are not realized (in long-term contracts) except in the final stages of the contract. Therefore, this requires the parties to the contract to leave some elements open, including the price, because the adoption of a fixed price and inflexible will not be appropriate to meet their desires when contracting, especially with ignorance of matters beyond their will and may affect the market conditions, and the possibility of modifying the fixed price through The elimination is very limited, especially when the parties to the contract are equally in terms of economic strength. Hence, in order to respond to market uncertainties, the

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Publication Date
Tue Mar 30 2010
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
PC-Based Controller for Shell and Tube Heat Exchanger
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PC-based controller is an approach to control systems with Real-Time parameters by controlling selected manipulating variable to accomplish the objectives. Shell and tube heat exchanger have been identified as process models that are inherently nonlinear and hard to control due to unavailability of the exact models’ descriptions. PC and analogue input output card will be used as the controller that controls the heat exchanger hot stream to the desired temperature.
The control methodology by using four speed pump as manipulating variable to control the temperature of the hot stream to cool to the desired temperature.
In this work, the dynamics of cross flow shell and tube heat exchanger is modeled from step changes in cold water f

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Publication Date
Thu Jun 20 2019
Journal Name
Baghdad Science Journal
Taxonomy of Memory Usage in Swarm Intelligence-Based Metaheuristics
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Metaheuristics under the swarm intelligence (SI) class have proven to be efficient and have become popular methods for solving different optimization problems. Based on the usage of memory, metaheuristics can be classified into algorithms with memory and without memory (memory-less). The absence of memory in some metaheuristics will lead to the loss of the information gained in previous iterations. The metaheuristics tend to divert from promising areas of solutions search spaces which will lead to non-optimal solutions. This paper aims to review memory usage and its effect on the performance of the main SI-based metaheuristics. Investigation has been performed on SI metaheuristics, memory usage and memory-less metaheuristics, memory char

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Publication Date
Wed Jan 01 2020
Journal Name
Ieee Access
Fast Temporal Video Segmentation Based on Krawtchouk-Tchebichef Moments
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Publication Date
Wed Jan 01 2025
Journal Name
Lecture Notes In Networks And Systems
Symlet Analysis for ECG-Based Diagnosis of Heart Dysfunction
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