Neural network-based encoder and decoder are one of the emerging techniques for image compression. To improve the compression rate, these models use a special module called the quantizer that improves the entropy of t...
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In recent years,there has been a significant increase in the number of people suffering from eye illnesses,which should be treated as soon as possible in order to avoid *** Fundus images are employed for this purpose,...
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In recent years,there has been a significant increase in the number of people suffering from eye illnesses,which should be treated as soon as possible in order to avoid *** Fundus images are employed for this purpose,as well as for analysing eye abnormalities and diagnosing eye *** can be recognised as bright lesions in fundus pictures,which can be thefirst indicator of diabetic *** that in mind,the purpose of this work is to create an Integrated Model for Exudate and Diabetic Retinopathy Diagnosis(IM-EDRD)with multi-level *** model uses Support Vector Machine(SVM)-based classification to separate normal and abnormal fundus images at thefirst *** input pictures for SVM are pre-processed with Green Channel Extraction and the retrieved features are based on Gray Level Co-occurrence Matrix(GLCM).Furthermore,the presence of Exudate and Diabetic Retinopathy(DR)in fundus images is detected using the Adaptive Neuro Fuzzy Inference System(ANFIS)classifier at the second level of *** detection,blood vessel extraction,and Optic Disc(OD)detection are all processed to achieve suitable ***,the second level processing comprises Morphological Component Analysis(MCA)based image enhancement and object segmentation processes,as well as feature extraction for training the ANFIS classifier,to reliably diagnose ***,thefindings reveal that the proposed model surpasses existing models in terms of accuracy,time efficiency,and precision rate with the lowest possible error rate.
The use of management by objectives (MBOs) methodologies, particularly the objectives and key results (OKRs) framework, has gained widespread attention in recent years as a means of improving organizational performanc...
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Post Quantum Cryptography has received an increasing amount of active research. This has been made prominent by the ever-growing field of quantum computing which poses a formidable threat to the modern cybersecurity l...
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Generating financial reports from a piece of news is a challenging task due to the lack of sufficient background knowledge to effectively generate long financial reports. To address this issue, this article proposes a...
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Subspace clustering has shown great potential in discovering the hidden low-dimensional subspace structures in high-dimensional data. However, most existing methods still face the problem of noise distortion and overl...
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Agriculture encompasses a way of life and a profession for the general population. Most global traditions and cultures revolve around agriculture. With the help of advanced farming, agriculture may become more profita...
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For providing enhanced authentication performance, the concept of multi-biometrics authentication systems has emerged as a promising solution in today’s digital era. In the existing literature, numerous studies were ...
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Understanding the learner’s requirements and status is important for recommending relevant and appropriate learning materials to the learner in personalized learning. For this purpose, the learning recommendatio...
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The objective of this research is to examine the use of feature selection and classification methods for distinguishing different types of brain *** brain tumor is characterized by an anomalous proliferation of brain c...
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The objective of this research is to examine the use of feature selection and classification methods for distinguishing different types of brain *** brain tumor is characterized by an anomalous proliferation of brain cells that can either be benign or *** tumors are misdiagnosed due to the variabil-ity and complexity of lesions,which reduces the survival rate in ***-sis of brain tumors via computer vision algorithms is a challenging *** and classification of brain tumors are currently one of the most essential surgical and pharmaceutical *** brain tumor identi-fication techniques require manual segmentation or handcrafted feature extraction that is error-prone and *** the proposed research work is mainly focused on medical image processing,which takes Magnetic Resonance Imaging(MRI)images as input and performs preprocessing,segmentation,fea-ture extraction,feature selection,similarity measurement,and classification steps for identifying brain ***,the medianfilter is practically applied to the input image to reduce the *** graph-cut segmentation technique is used to segment the tumor *** texture feature is extracted from the output of the segmented *** extracted feature is selected by using the Ant Colony Opti-mization(ACO)algorithm to improve the performance of the classifi*** prob-abilistic approach is used to solve computing *** Euclidean distance is used to calculate the degree of similarity for each extracted *** selected feature value is given to the Relevance Vector Machine(RVM)which is a multi-class classification ***,the tumor is classified as abnormal or *** experimental result reveals that the proposed RVM technique gives a better accuracy range of 98.87%when compared to the traditional Support Vector Machine(SVM)technique.
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