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.
Arabic text categorization for pattern recognitions is challenging. We propose for the first time a novel holistic method based on clustering for classifying Arabic writer. The categorization is accomplished stage-wise. Firstly, these document images are sectioned into lines, words, and characters. Secondly, their structural and statistical features are obtained from sectioned portions. Thirdly, F-Measure is used to evaluate the performance of the extracted features and their combination in different linkage methods for each distance measures and different numbers of groups. Finally, experiments are conducted on the standard KHATT dataset of Arabic handwritten text comprised of varying samples from 1000 writers. The results in the generatio
... Show MoreResearchers are increasingly using multimodal biometrics to strengthen the security of biometric applications. In this study, a strong multimodal human identification model was developed to address the growing problem of spoofing attacks in biometric security systems. Through the use of metaheuristic optimization methods, such as the Genetic Algorithm(GA), Ant Colony Optimization(ACO), and Particle Swarm Optimization (PSO) for feature selection, this unique model incorporates three biometric modalities: face, iris, and fingerprint. Image pre-processing, feature extraction, critical image feature selection, and multibiometric recognition are the four main steps in the workflow of the system. To determine its performance, the model wa
... Show MoreRecently, biometric technologies are used widely due to their improved security that decreases cases of deception and theft. The biometric technologies use physical features and characters in the identification of individuals. The most common biometric technologies are: Iris, voice, fingerprint, handwriting and hand print. In this paper, two biometric recognition technologies are analyzed and compared, which are the iris and sound recognition techniques. The iris recognition technique recognizes persons by analyzing the main patterns in the iris structure, while the sound recognition technique identifies individuals depending on their unique voice characteristics or as called voice print. The comparison results show that the resul
... Show MoreThat researchers in the play Science Find a theatrical form of an experimental creative, and these experiences taken from the innovation space aesthetic dialogue with the receiver, especially since with previous theatrical experience and is an extension of her, because the interactive theater theatrical terms that assume a pattern do from the depth of the relationship between supply playwright and the audience, which alters the receiving skills actually change, and to monitor these differing divided into three classes that include research, methodological framework (Chapter I) and includes, research problem, the importance of research and the need to him, the goal of the research, the limits Find it border, and the theoretical framework
... Show MoreL’Enfer est un roman de chambre par excellence. Tous les événements s'y sont presque déroulés. Le sujet de ce roman se résume: un jeune homme quitte la campagne pour vivre à Paris .Il loue une chambre dans un hôtel. Il tombe, par un pur hasard, sur une fente dans le mur de sa par laquelle chambre il peut voir tout ce qui se passe dans la chambre voisine .L'histoire racontée par ce narrateur, est la vie intime des couples venant dans cette chambre. Il médite sur sa propre condition à la lumière de ce qui se déroule dans la chambre voisine .C'est pour cette raison,que le roman se caractérise par une stabilité.Quoi qu’elle soit manifeste, le héros démontre une mobilité à son niveau psychique. Car il y a une évolution
... Show MoreAutomation is one of the key systems in modern agriculture, providing potential solutions to the challenges related to the growing world population, demographic shifts, and economic situation. The present article aims to highlight the importance of precision agriculture (PA) and smart agriculture (SA) in increasing agricultural production and the importance of environmental protection in increasing production and reducing traditional production. For this purpose, different types of automation systems in the field of agricultural operations are discussed, as well as smart agriculture technologies including the Internet of Things (IoT), artificial intelligence (AI), machine learning (ML), big data analysis, in addition to agricultural robots,
... Show MoreThis research aims to analyze and simulate biochemical real test data for uncovering the relationships among the tests, and how each of them impacts others. The data were acquired from Iraqi private biochemical laboratory. However, these data have many dimensions with a high rate of null values, and big patient numbers. Then, several experiments have been applied on these data beginning with unsupervised techniques such as hierarchical clustering, and k-means, but the results were not clear. Then the preprocessing step performed, to make the dataset analyzable by supervised techniques such as Linear Discriminant Analysis (LDA), Classification And Regression Tree (CART), Logistic Regression (LR), K-Nearest Neighbor (K-NN), Naïve Bays (NB
... Show MoreIn this paper three techniques for image compression are implemented. The proposed techniques consist of three dimension (3-D) two level discrete wavelet transform (DWT), 3-D two level discrete multi-wavelet transform (DMWT) and 3-D two level hybrid (wavelet-multiwavelet transform) technique. Daubechies and Haar are used in discrete wavelet transform and Critically Sampled preprocessing is used in discrete multi-wavelet transform. The aim is to maintain to increase the compression ratio (CR) with respect to increase the level of the transformation in case of 3-D transformation, so, the compression ratio is measured for each level. To get a good compression, the image data properties, were measured, such as, image entropy (He), percent root-
... Show MoreMulti-walled carbon nanotubes from cheap tubs company MWCNT-CP were purified by alcohol \ H2O2 \ separation funnel which is simple, easy and scalable techniques. The steps of purification were characterized by X-ray diffraction, Raman spectroscopy, scanning electron microscopy SEM with energy dispersive of X-ray spectroscopy EDX and surface area measurements. The technique was succeeded to remove most the trace element from MWCNT-CP which causing increase the surface area. The ratios of impurities were reduced to less 0.6% after treatment by three steps with losing less than 5% from MWCNT-CP.