Research ArticleOpen accessEvery word in the titleNovel Depression Classification Framework Using Optimal Feature Integration with Hybrid Convolution (1D/3D) Based Adaptive Residual DenseNetB. Manjulatha, Suresh PabbojuThis study introduces a novel depression classification method by incorporating multimodal data to reduce this limitation and improve the accuracy of depression diagnosis. In the beginning, the multimodal data such as speech signal, Electroencephalographic (EEG), and text data is obtained from the benchmark datasets. These acquired text data are subjected to the text pre-processing phase, where the stemming, character removal, … …Journal of Computer Science, Vol. 21, Issue 3 · 25 Feb 2025 · 5,860 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleClassification of Finger Vein Image Using Convolutional Neural NetworkAhmed S. Hameed, Shawkat K. Guirguis, Hend A. ElsayedCurrently available technologies can perform rather well, but their effectiveness is mostly contingent on how well the venous images being analyzed are quality images. Finger vein features have garnered significant attention in the past few years as a potential means of automatic user identification. A significant amount of daily usage goes into the very vital personal identification procedure. The identification … …Journal of Computer Science, Vol. 21, Issue 2 · 6 Jan 2025 · 4,712 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleFacial Recognition and Discovery Using Convolution Deep Learning Neural NetworkAbdel Karim Mohamed BaarehFacial recognition is a critical and well-established topic that has caught the interest of researchers across various application areas. Face detection and identification are critical components of human detection systems. Researchers in different fields used numerous techniques to recognize human faces in various positions considering several features, many results were also obtained. In this research, we aim to use a … …Journal of Computer Science, Vol. 20, Issue 11 · 22 Oct 2024 · 5,243 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleConvolution Neural Networks of Dynamically Sized Filters with Modified Stochastic Gradient Descent Optimizer for Sound ClassificationManu Pratap Singh, Pratibha RashmiDeep Neural Networks (DNNs), specifically Convolution Neural Networks (CNNs) are found well suited to address the problem of sound classification due to their ability to capture the pattern of time and frequency domain. Mostly the convolutional neural networks are trained and tested with time-frequency patches of sound samples in the form of 2D pattern vectors. Generally, existing pre-trained convolutional neural … …Journal of Computer Science, Vol. 20, Issue 1 · 13 Dec 2023 · 5,781 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleDiagnosing Alzheimer’s Disease using Convolution Neural NetworksSarita, Saurabh Mukherjee, Tanupriya Choudhury et al.Alzheimer’s is a disease wherein constant degeneration of neurons and their synapses result in impaired brain functioning which leads to personality changes, memory loss, thinking and speech disorder. So, there is a requirement of an automated and early diagnosis of this disease to decrease the death rate. The proposed work is coupled with deep learning techniques to predict the Alzheimer’s … …Journal of Computer Science, Vol. 18, Issue 2 · 21 Feb 2022 · 7,344 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleConvSVD++: A Hybrid Deep CF Recommender Model using Convolutional Neural NetworkMohamed Grida, Lamiaa Fayed, Mohamed HassanRecommender systems are powerful systems that give added value to business and corporation. They are relatively recent technology and they will only keep improving in the future. The most widely used algorithms for recommender systems are categorized into the traditional recommender and deep-based recommender system. The traditional recommendation algorithm suffers from sparse data that significantly degrades recommendation accuracy. The hybrid … …Journal of Computer Science, Vol. 16, Issue 12 · 13 Jan 2021 · 6,731 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleThermal Face Authentication with Convolutional Neural NetworkMohamed Sayed, Faris BakerMatching thermal face images as a method of biometric authentication has gained increasing interest because of its advantage of tracking a target object at night and in total darkness. Therefore, for security purposes, it has become highly favourable and has extensive applications, for instance, in video surveillance at night. The aim of this study is to present a simple and … …Journal of Computer Science, Vol. 14, Issue 12 · 10 Dec 2018 · 7,854 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleESTIMATING LOSS SEVERITY DISTRIBUTION: CONVOLUTION APPROACHRo J. PakFinancial loss can be classified into two types such as expected loss and unexpected loss. A current definition seeks to separate two losses from a total loss. In this article, however, we redefine a total loss as the sum of expected and unexpended losses; then the distribution of loss can be considered as the convolution of the distributions of both … …Journal of Mathematics and Statistics, Vol. 10, Issue 2 · 2 May 2014 · 6,896 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleSpeckle Suppression of Radar Images Using Normalized ConvolutionA. K. Helmy, G. S. El-TaweelProblem statement: Synthetic Aperture Radar (SAR) images are becoming more widely used in remote sensing applications. SAR uses microwave radiation to illuminate the earth's surface. The coherent microwave illumination, however, suffers from fading effects result in generating a multiplicative speckle noise that corrupts SAR images. Approach: Through this study, scheme to reduce speckles was proposed, it was designed to accomplish … …Journal of Computer Science, Vol. 6, Issue 10 · 5 Aug 2010 · 7,259 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleOn New Bijective Convolution Operator Acting for Analytic FunctionsOqlah Al-Refai, Maslina DarusProblem statement: We introduced a new bijective convolution linear operator defined on the class of normalized analytic functions. This operator was motivated by many researchers namely Srivastava, Owa, Ruscheweyh and many others. The operator was essential to obtain new classes of analytic functions. Approach: Simple technique of Ruscheweyh was used in our preliminary approach to create new bijective convolution linear … …Journal of Mathematics and Statistics, Vol. 5, Issue 1 · 31 Mar 2009 · 8,965 accessesView PDFCite