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Research ArticleOpen accessIn the abstractAutomated Face Detection, Recognition and Gender Estimation Applied to Person IdentificationMd Hannan, Md Rafiqul Islam, Md Ashraful Haque et al.Face detection, recognition and gender estimation are one of the most significant research areas in computer vision, not only because of the challenging nature of faces as an object but also due to the countless applications that require the application of face detection, tracking and recognition. Although many significant types of research on face detection, recognition and gender estimation problems … …Journal of Computer Science, Vol. 15, Issue 3 · 27 Mar 2019 · 9,492 accessesView PDFCite
Research ArticleOpen accessIn the abstractRadial Basis Function Neural Networks Towards Electronic Trust QuantificationSmitha Zacaria, Tiny du ToitTrust is a broad term applicable in various contexts. Trust between electronic entities is complex to quantify, particularly in intricate networks. Traditional trust algorithms rely on historical trust values, requiring storage and access to past transaction details. Contextual variations further complicate trust calculation. Challenges in calculating trust include heightened computational complexities, managing information storage, and securing access to extensive datasets … …Journal of Computer Science, Vol. 20, Issue 11 · 26 Sep 2024 · 4,791 accessesView PDFCite
Research ArticleOpen accessIn the abstractDistributional Models with Syntactic Contexts for the Measurement of Word Similarity in Brazilian PortugueseEduardo E. Berlitz, Denis A. Araujo, Allan B. Silva et al.The similarity between words constitutes significant support to tasks in natural language processing. Several works use Lexical resources such as WordNet for semantic similarity and synonym identification. Nevertheless, words out-of-vocabulary or missing links between senses are perceived problems of this approach. Distributional-based proposals like word embeddings have successfully been used to meet such problems, but the lack of contextual information … …Journal of Computer Science, Vol. 15, Issue 10 · 31 May 2019 · 6,818 accessesView PDFCite
Research ArticleOpen accessIn the abstractAn Enhanced Training- Based Arabic Sign Language Virtual Interpreter Using Parallel Recurrent Neural NetworksMohamed A. AbdouIntelligent machine translation systems have a remarkable importance in integrating people with disabilities in community. Arabic to Arabic sign language systems are limited. Deep Learning (DL) was successfully applied to problems related to music information retrieval, image recognition and text recognition, but its use in sign language recognition is rare. This paper introduces an automatic virtual translation system from Arabic … …Journal of Computer Science, Vol. 14, Issue 2 · 20 Feb 2018 · 7,628 accessesView PDFCite
Research ArticleOpen accessIn the abstractFuzzy ARTMAP Approach for Arabic Writer Identification using Novel Features FusionTanzila SabaArabic writer identification and associated tasks are still fresh due to huge variety of Arabic writer's styles. Current research presents a fusion of statistical features, extracted from fragments of Arabic handwriting samples to identify the writer using fuzzy ARTMAP classifier. Fuzzy ARTMP is supervised neural model, especially suited to classification problems. It is faster to train and need less number … …Journal of Computer Science, Vol. 14, Issue 2 · 7 Feb 2018 · 8,305 accessesView PDFCite
Research ArticleOpen accessIn the abstractAnalyzing Effect on Residual Learning by Gradual Narrowing Fully-Connected Layer Width and Implementing Inception Block in Convolution LayerSaurabh SharmaResearch conducted on the advancement of CNN architecture for computer vision problems focuses on strategically choosing and modifying convolution hyperparameters (kernel, pooling, etc.). However, these research works don't exploit the advantage of employing multi fully-connected layers post the core schema to avail further performance improvements, which have been identified as the first research gap. Studies were also conducted to address … …Journal of Computer Science, Vol. 18, Issue 5 · 24 May 2022 · 6,044 accessesView PDFCite
Research ArticleOpen accessIn the abstractRandom Forest Classification and Support Vector Machine for Detecting Epilepsyusing Electroencephalograph RecordsHeri Kuswanto, Mutiah Salamah, Muhammad Idrus FachruddinComplexity in data structure has led to the rapid development of computational statistics methods. Machine learning approaches have been introduced and applied to solve complex problems in many fields. This paper applies two common machine learning approaches, Random Forest (RF) and Support Vector Machine (SVM), in the detection of epilepsy. The diagnosis of epilepsy can usually only be made when … …American Journal of Applied Sciences, Vol. 14, Issue 5 · 4 May 2017 · 8,134 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Guideline of using Assistive Technologies and Educational Services for Students with Disabilities in Higher EducationTheeratorn Lersilp, Suchitporn LersilpAssistive Technologies (AT) and Educational Services (ES) are important in the needs of students with disabilities in higher education and their availability should be studied to provide appropriate help for them. The objectives of this study were to explore the problems in using AT and ES for these students and develop a guideline from the perspective of key informants. Data … …American Journal of Applied Sciences, Vol. 14, Issue 5 · 28 Apr 2017 · 7,564 accessesView PDFCite
EditorialOpen accessIn the abstractCommentary-How do we Improve Training for Receptor Research?Marilee Ann BenoreThis issue of the American Journal of Biochemistry and Biotechnology features articles about receptor-ligand interactions that are critical to the wellbeing of all living organisms. The importance of the field of receptor research is supported by the large number of articles published in journals, the numerous specialty journals, the international conferences and the percentage of legal drugs on the market … …American Journal of Biochemistry and Biotechnology, Vol. 11, Issue 4 · 8 Dec 2015 · 8,056 accessesView PDFCite
Research ArticleOpen accessIn the abstractAn Evolving Autoregressive Predictor for Time Series ForecastingDe Z. Li, Wilson Wang, Fathy IsmailAutoregressive (AR) model is a common predictor that has been extensively used for time series forecasting. Many training methods can used to update AR model parameters, for instance, least square estimate and maximum likelihood estimate; however, both techniques are sensitive to noisy samples and outliers. To deal with the problems, an evolving AR predictor, EAR, is developed in this study … …American Journal of Engineering and Applied Sciences, Vol. 8, Issue 1 · 8 Apr 2015 · 6,965 accessesView PDFCite