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Research ArticleOpen accessIn the abstractThermal 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 accessIn the abstractPredicting Students’ Academic Performance in the University Using Meta Decision Tree ClassifiersShanthini A., G. Vinodhini, R.M. ChandrasekaranStudent performance prediction is an area of concern for educational institutions. At the University level learning system, the method or rule adopted to identify the candidates who pass or fail differs depending on various factors such as the course, the department of study and so on. Predicting the result of a student in a course is an issue that has … …Journal of Computer Science, Vol. 14, Issue 5 · 28 Feb 2018 · 9,194 accessesView PDFCite
Research ArticleOpen accessIn the abstractStatistical Pattern Recognition for Thresholding between Human Skin and Background in Color ImagesRafael Divino Ferreira Feitosa, Vinícius Araújo Santos, Leandro Luís Galdino de Oliveira et al.Many research works based on the tone of human skin have been developed to locate and track the human body for the purpose of recognition in color images. With respect to other techniques, some advantages of face detection based on skin color are the smaller processing time, invariant angles of rotation and the performance in semi-occluded faces. In this study … …Journal of Computer Science, Vol. 13, Issue 2 · 10 Apr 2017 · 7,923 accessesView PDFCite
EditorialOpen accessIn the abstractBig Data and Parkinson’s Disease - from Understanding of Disease to Personalised MedicineYen F. Tai, Nicola PaveseThe advancement of information technology in recent years has generated a huge amount of datasets in all areas of scientific research. This has led to new opportunities to harness the 'Big Data' to improve our understanding of diseases - from investigating disease mechanisms to monitoring treatment responses. The Big Data approach is a data-driven and often hypothesis-free, way of studying … …Neuroscience International, Vol. 7, Issue 1 · 27 Jul 2016 · 7,755 accessesView PDFCite
InvestigationOpen accessIn the abstractBackpropagation Vs. Radial Basis Function Neural Model: Rainfall Intensity Classification For Flood Prediction Using Meteorology DataSoo See Chai, Wei Keat Wong, Kok Luong GohRainfall is one of the important weather variables that vary in space and time. High mean daily rainfall (>30 mm) has a high possibility of resulting in flood. Accurate prediction of this variable would save human lives and properties. Soft computing methods have been widely applied in this field. Among the various soft computing methods, Artificial Neural Network (ANN) is … …Journal of Computer Science, Vol. 12, Issue 4 · 15 Apr 2016 · 8,705 accessesView PDFCite
Research ArticleOpen accessIn the abstractANALYSIS OF BAYESIAN CLASSIFIER ACCURACYFelipe Schneider Costa, Maria Marlene De Souza Pires, Silvia Modesto NassarThe naïve Bayes classifier is considered one of the most effective classification algorithms today, competing with more modern and sophisticated classifiers. Despite being based on unrealistic (naïve) assumption that all variables are independent, given the output class, the classifier provides proper results. However, depending on the scenario utilized (network structure, number of samples or training cases, number of variables), the … …Journal of Computer Science, Vol. 9, Issue 11 · 26 Sep 2013 · 8,375 accessesView PDFCite
Research ArticleOpen accessIn the abstractFace Biometrics Based on Principal Component Analysis and Linear Discriminant AnalysisLih-Heng Chan, Sh-Hussain Salleh, Chee-Ming TingProblem statement: In facial biometrics, face features are used as the required human traits for automatic recognition. Feature extracted from face images are significant for face biometrics system performance. Approach: In this thesis, a framework of facial biometric was designed based on two subspace methods i.e., Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA). First, PCA is used for … …Journal of Computer Science, Vol. 6, Issue 7 · 31 Jul 2010 · 7,664 accessesView PDFCite
Research ArticleOpen accessIn the abstractBayesian Regularization in a Neural Network Model to Estimate Lines of Code Using Function PointsK. K. Aggarwal, Yogesh Singh, Pravin Chandra, Manimala PuriIt is a well known fact that at the beginning of any project, the software industry needs to know, how much will it cost to develop and what would be the time required ? . This paper examines the potential of using a neural network model for estimating the lines of code, once the functional requirements are known. Using the … …Journal of Computer Science, Vol. 1, Issue 4 · 31 Dec 2005 · 30,191 accessesView PDFCite
Research ArticleOpen accessAll words, across the recordEnhancing E-Banking Security and Personalization through Convolutional Neural Network-Based Facial RecognitionRamy Kamal Amin, Ghada A. El Khayat, Farid El Sahn, Abeer A. AmerFacial recognition technology has become a cornerstone in enhancing the security and user experience of electronic banking services. Its ability to provide a seamless yet secure authentication method is vital in combating fraud and maintaining the integrity of online financial transactions. This study presents the development of an advanced electronic banking system that strengthens security through the integration of a … …Journal of Computer Science, Vol. 21, Issue 10 · 7 Dec 2025 · 3,310 accessesView PDFCite
Research ArticleOpen accessAll words, across the recordA Multi-Split Cross-Strategy for Enhancing Machine Learning Algorithms Prediction Results with Data Generated by Conditional Generative Adversarial NetworkAbdelfattah Abassi, Brahim Bakkas et al.In this study, we present a Multi-Split Cross-Strategy (MSC-Strategy) designed to leverage synthetic tabular data generated by a Conditional Generative Adversarial Network (CGAN). Our study aims to investigate the potential of synthetic data in comparison to real-world data for improving machine learning predictive results. Firstly, we develop a CGAN architecture tailored to generate synthetic tabular data, trained on a comprehensive … …Journal of Computer Science, Vol. 20, Issue 7 · 9 Apr 2024 · 6,695 accessesView PDFCite