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49 results for “Learning Speed”
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Research ArticleOpen accessIn the abstractImproving the Performance of Backpropagation Neural Network Algorithm for Image Compression/Decompression SystemOmaima N.A. AL-AllafProblem statement: The problem inherent to any digital image is the large amount of bandwidth required for transmission or storage. This has driven the research area of image compression to develop algorithms that compress images to lower data rates with better quality. Artificial neural networks are becoming attractive in image processing where high computational performance and parallel architectures are required. … …Journal of Computer Science, Vol. 6, Issue 11 · 26 Oct 2010 · 8,370 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Performance Study of Reactive Multicast Routing Protocols in Virtual Class Room Using Mobile Ad Hoc NetworkS. Vijayaragavan, K. Duraiswamy, B. Kalaavathi, S. MadhaviProblem statement: A great deal of excitement has recently propelled Mobile Learning to the forefront of educational technology. The exponential growth of mobile technology in the recent years, increase in the availability of high-bandwidth network, advances in wireless technologies and popularity of handheld devices, have opened up new accessibility opportunities for education. Approach: Virtual class room using MANET had been … …Journal of Computer Science, Vol. 5, Issue 11 · 30 Nov 2009 · 6,875 accessesView PDFCite
Research ArticleOpen accessIn the abstractTowards a Generic Multimodal Architecture for Batch and Streaming Big Data IntegrationSiham Yousfi, Maryem Rhanoui, Dalila ChiadmiBig Data are rapidly produced from various heterogeneous data sources. They are of different types (text, image, video or audio) and have different levels of reliability and completeness. One of the most interesting architectures that deal with the large amount of emerging data at high velocity is called the lambda architecture. In fact, it combines two different processing layers namely … …Journal of Computer Science, Vol. 15, Issue 1 · 31 Jan 2019 · 7,646 accessesView PDFCite
Review ArticleOpen accessIn the abstractComparative Analysis of Classical Feature Detection Methods for UAV-Based Tomato DetectionMuhammad Sarwar Jahan Morshed, Md. Nasim Adnan, Md. Rafiqul IslamRemote sensing technologies, especially Unmanned Aerial Vehicles (UAVs), become crucial for Precision Agriculture (PA) to perform different tasks such as crop detection, yield prediction, leaf disease diagnosis, weed detection, and harvest forecasting to ensure higher productivity. Therefore, using various image analytics methods feature detection from the UAV-captured images plays a vital role for conducting these PA tasks. To enhance the … …Journal of Computer Science, Vol. 21, Issue 9 · 7 Nov 2025 · 2,404 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
EditorialOpen accessIn the abstractData Mining in Time Series: Current Study and Future TrendTan Yan, Liudmila Ulanova, Ye Ouyang, Fengyuan XuTime series represent sequences of data points where usually their order is defined by the time when they were recorded. Thus, virtually any sequential recordings can be stored as time series: Stock prices, weather conditions, physical system parameters change, product quality monitoring, etc. This leads to ubiquity of time series in all scientific and practical fields (Esling and Agon, 2012); … …Journal of Computer Science, Vol. 10, Issue 12 · 26 Jan 2015 · 8,756 accessesView PDFCite
Research ArticleOpen accessIn the abstractA New Algorithm for Fractal Coding Using Self Organizing MapS. Bhavani, k. ThanushkodiProblem statement: In medical imaging, lossy compression schemes are generally not used due to possible loss of useful clinical information and also degradations may result in lossy compression owing to operations like enhancement. As the medical images are huge in size a good lossy compression technology is required to store them in medical archives in an economical manner. There is … …Journal of Computer Science, Vol. 8, Issue 6 · 15 Mar 2012 · 7,583 accessesView PDFCite
Research ArticleOpen accessIn the abstractAn Analysis of Power Aware Congestion Control Multipath Multicast Protocol for Mobile Ad hoc NetworkDuraiswamy Karuppaswamy, Vijayaragavan ShanmugamProblem statement: In MANETs, wireless link transmission errors, mobility and congestion are major causes for packet loss. Mobility may cause packet loss in different ways. Whereas congestion in a network occurs, whenever the demands exceed the maximum capacity of a communication link especially when multiple hosts try to access a shared media simultaneously. Approach: In this study, we proposed a … …Journal of Computer Science, Vol. 6, Issue 12 · 2 Nov 2010 · 7,038 accessesView PDFCite
Research ArticleOpen accessIn the abstractBoosting Kernel Discriminative Common Vectors for Face RecognitionC. Lakshmi, M. PonnavaikkoProblem statement: Kernel discriminative common vector (KDCV) was one of the most effective non-linear techniques for feature extraction from high dimensional data including images and text data. Approach: This study presented a new algorithm called Boosting Kernel Discriminative Common Vector (BKDCV) to further improve the overall performance of KDCV by integrating the boosting and KDCV techniques. Results: In BKDCV, the … …Journal of Computer Science, Vol. 5, Issue 11 · 30 Nov 2009 · 6,571 accessesView PDFCite
Research ArticleOpen accessIn the abstractGenetic Algorithm Based Probabilistic Motif Discovery in Unaligned Biological SequencesM. Hemalatha, K. VivekanandanFinding motif in biosequences is the most important primitive operation in computational biology. There are many computational requirements for a motif discovery algorithm such as computer memory space requirement and computational complexity. To overcome the complexity of motif discovery, we propose an alternative solution integrating genetic algorithm and Fuzzy Art machine learning approaches for eliminating multiple sequence alignment process. Problem … …Journal of Computer Science, Vol. 4, Issue 8 · 31 Aug 2008 · 6,729 accessesView PDFCite