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Automated Glaucoma Detection Techniques: A Literature Review
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Significant advances in the automated glaucoma detection techniques have been made through the employment of the Machine Learning (ML) and Deep Learning (DL) methods, an overview of which will be provided in this paper. What sets the current literature review apart is its exclusive focus on the aforementioned techniques for glaucoma detection using the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines for filtering the selected papers. To achieve this, an advanced search was conducted in the Scopus database, specifically looking for research papers published in 2023, with the keywords "glaucoma detection", "machine learning", and "deep learning". Among the multiple found papers, the ones focusing on ML and DL techniques were selected. The best performance metrics obtained using ML recorded in the reviewed papers, were for the SVM, which achieved accuracies of 98.31%, 98.61%, 96.43%, 96.67%, 95.24%, and 98.60% in the ACRIMA, REFUGE, RIM-ONE, ORIGA-light, DRISHTI-GS, and sjchoi86-HRF databases, respectively, employing the REFUGE-trained model, while when deploying the ACRIMA-trained model, it attained accuracies of 98.92%, 99.06%, 98.27%, 97.10%, 96.97%, and 96.36%, in the same databases, respectively. The best performance metrics obtained utilizing DL recorded in the reviewed papers, were for the lightweight CNN, with an accuracy of 99.67% in the Diabetic Retinopathy (DR) and 96.5% in the Glaucoma (GL) databases. In the context of non-healthy screening, CNN achieved an accuracy of 99.03% when distinguishing between GL and DR cases. Finally, the best performance metrics were obtained using ensemble learning methods, which achieved an accuracy of 100%, specificity of 100%, and sensitivity of 100%. The current review offers valuable insights for clinicians and summarizes the recent techniques used by the ML and DL for glaucoma detection, including algorithms, databases, and evaluation criteria.

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Publication Date
Sat Jan 01 2022
Journal Name
Indonesian Journal Of Electrical Engineering And Computer Science
Increasing validation accuracy of a face mask detection by new deep learning model-based classification
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During COVID-19, wearing a mask was globally mandated in various workplaces, departments, and offices. New deep learning convolutional neural network (CNN) based classifications were proposed to increase the validation accuracy of face mask detection. This work introduces a face mask model that is able to recognize whether a person is wearing mask or not. The proposed model has two stages to detect and recognize the face mask; at the first stage, the Haar cascade detector is used to detect the face, while at the second stage, the proposed CNN model is used as a classification model that is built from scratch. The experiment was applied on masked faces (MAFA) dataset with images of 160x160 pixels size and RGB color. The model achieve

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Publication Date
Sun Nov 19 2023
Journal Name
Aip Conference Proceedings
Designing a database for a three dimensional model using geomatics techniques
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Publication Date
Wed Jan 01 2025
Journal Name
Journal Of Cybersecurity And Information Management
A New Automated System Approach to Detect Digital Forensics using Natural Language Processing to Recommend Jobs and Courses
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A resume is the first impression between you and a potential employer. Therefore, the importance of a resume can never be underestimated. Selecting the right candidates for a job within a company can be a daunting task for recruiters when they have to review hundreds of resumes. To reduce time and effort, we can use NLTK and Natural Language Processing (NLP) techniques to extract essential data from a resume. NLTK is a free, open source, community-driven project and the leading platform for building Python programs to work with human language data. To select the best resume according to the company’s requirements, an algorithm such as KNN is used. To be selected from hundreds of resumes, your resume must be one of the best. Theref

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Publication Date
Mon Apr 03 2023
Journal Name
Journal Of Al-qadisiyah For Computer Science And Mathematics
A General Overview on the Categories of Image Features Extraction Techniques: A Survey
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In the image processing’s field and computer vision it’s important to represent the image by its information. Image information comes from the image’s features that extracted from it using feature detection/extraction techniques and features description. Features in computer vision define informative data. For human eye its perfect to extract information from raw image, but computer cannot recognize image information. This is why various feature extraction techniques have been presented and progressed rapidly. This paper presents a general overview of the feature extraction categories for image.

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Publication Date
Thu Dec 29 2022
Journal Name
Iraqi Journal Of Computer, Communication, Control And System Engineering
Combinatorial Testing Approaches: A Systematic Review
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Testing is a vital phase in software development, and having the right amount of test data is an important aspect in speeding up the process. As a result of the integrationist optimization challenge, extensive testing may not always be practicable. There is also a shortage of resources, expenses, and schedules that impede the testing process. One way to explain combinational testing (CT) is as a basic strategy for creating new test cases. CT has been discussed by several scholars while establishing alternative tactics depending on the interactions between parameters. Thus, an investigation into current CT methods was started in order to better understand their capabilities and limitations. In this study, 97 publications were evalua

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Publication Date
Thu Mar 30 2023
Journal Name
Iraqi Journal Of Computer, Communication, Control And System Engineering
Data Analytics and Blockchain: A Review
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Blockchain technology relies on cryptographic techniques that provide various advantages, such as trustworthiness, collaboration, organization, identification, integrity, and transparency. Meanwhile, data analytics refers to the process of utilizing techniques to analyze big data and comprehend the relationships between data points to draw meaningful conclusions. The field of data analytics in Blockchain is relatively new, and few studies have been conducted to examine the challenges involved in Blockchain data analytics. This article presents a systematic analysis of how data analytics affects Blockchain performance, with the aim of investigating the current state of Blockchain-based data analytics techniques in research fields and

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Publication Date
Fri Nov 18 2022
Journal Name
International Journal Of Nanoscience
Plasma Production and Applications: A Review
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Large amounts of plasma, the universe’s fourth most common kind of stuff, may be found across our galaxy and other galaxies. There are four types of matter in the cosmos, and plasma is the most common. By heating the compressed air or inert gases to create negatively and positively charged particles known as ions, electrically neutral particles in their natural state are formed. Many scientists are currently focusing their efforts on the development of artificial plasma and the possible advantages it may have for humankind in the near future. In the literature, there is a scarcity of information regarding plasma applications. It’s the goal of this page to describe particular methods for creating and using plasma, which may be us

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Publication Date
Tue Apr 01 2025
Journal Name
Journal Of Economics And Administrative Sciences
Spatial Quantile Autoregressive Model: A Review
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This paper is specifically a detailed review of the Spatial Quantile Autoregressive (SARQR) model that refers to the incorporation of quantile regression models into spatial autoregressive models to facilitate an improved analysis of the characteristics of spatially dependent data. The relevance of SARQR is emphasized in most applications, including but not limited to the fields that might need the study of spatial variation and dependencies. In particular, it looks at literature dated from 1971 and 2024 and shows the extent to which SARQR had already been applied previously in other disciplines such as economics, real estate, environmental science, and epidemiology. Accordingly, evidence indicates SARQR has numerous benefits compar

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Publication Date
Sun Jun 24 2018
Journal Name
Journal Of Pharmacy Research
Transdermal drug delivery system: A review
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Transdermal drug delivery has made an important contribution to medical practice but has yet to fully achieve its potential as an alternative to oral delivery and hypodermic injections. Transdermal therapeutic systems have been designed to provide controlled continuous delivery of drugs through the skin to the systemic circulation. A transdermal patch is an adhesive patch that has a coating of drug; the patch is placed on the skin to deliver particular amount of drug into the systemic circulation over a period of time. The transdermal drug delivery systems (TDDS) review articles provide information regarding the transdermal drug delivery systems and its evaluation process as a ready reference for the research scientist who is involved

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Publication Date
Mon Mar 08 2021
Journal Name
Iraqi Journal For Electrical And Electronic Engineering
No Mobile Phobia Phenomenon _ A Review
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The No Mobile Phone Phobia or Nomophobia notion is referred to the psychological condition once humans have a fear of being disconnected from mobile phone connectivity. Hence, it is considered as a recent age phobia that emerged nowadays as a consequence of high engagement between people, mobile data, and communication inventions, especially the smart phones. This review is based on earlier observations and current debate such as commonly used techniques that modeling and analyzing this phenomenon like statistical studies. All that in order to possess preferable comprehension concerning human reactions to the speedy technological ubiquitous. Accordingly, humans ought to restrict their utilization of mobile phones instead of prohibit

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