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82 results for “Learning Parameters”
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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 abstractDirect Model Reference Adaptive Controller Based-On Neural-Fuzzy Techniques for Nonlinear Dynamical SystemsHafizah Husain, Marzuki Khalid, Rubiyah YusofThis paper presents a direct neural-fuzzy-based Model Reference Adaptive Controller (MRAC) for nonlinear dynamical systems with unknown parameters. The two-phase learning is implemented to perform structure identification and parameter estimation for the controller. In the first phase, similarity index-based fuzzy c-means clustering technique extracts the fuzzy rules in the premise part for the neural-fuzzy controller. This technique enables the recruitment … …American Journal of Applied Sciences, Vol. 5, Issue 7 · 31 Jul 2008 · 6,939 accessesView PDFCite
Research ArticleOpen accessIn the abstractConvolution 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 accessIn the abstractDetection of Rotten Fresh-Cut Cauliflowers based on Machine Vision Technology and Watershed Segmentation MethodJianxin Xue, Liang Huang, Bingyu Mu et al.In this study, machine vision technology was used to separate the samples and detect the rotting degrees of fresh-cut cauliflowers. First, the improved watershed algorithm was used for the segmentation of fresh-cut cauliflower samples and the extraction of single-sample. Then, three color models, a gray co-occurrence matrix and two feature extraction algorithms were used to extract the color, texture and … …American Journal of Biochemistry and Biotechnology, Vol. 18, Issue 2 · 13 Apr 2022 · 6,083 accessesView PDFCite
Research ArticleOpen accessIn the abstractA New Methodology for Neural Network Training Ensures Error Reduction in Time Series ForecastingPaola A. Sánchez-Sánchez, José Rafael García-GonzálezArtificial Neural Networks (ANN) consists of some components, such as architecture and learning algorithm. These components have a significant effect on the performance of the ANN, but finding good parameters is a difficult task to achieve. An important requirement for this task is to ensure the reduction of error when inputs and/or hidden neurons are added. In practice, it is … …Journal of Computer Science, Vol. 13, Issue 7 · 4 Jul 2017 · 7,171 accessesView PDFCite
Research ArticleOpen accessIn the abstractFine-Tuned MobileNet Classifier for Classification of Strawberry and Cherry Fruit TypesVenkatesh, Nagaraju Yallappa, Siddhanth Udayashankar Hegde, Sangeetha Raj StalinThis paper proposed an accurate, fast and reliable strawberry, cherry fruit detection and classification system for the automated strawberry cherry yield estimation. State-of-the-art deep learning-based fine-tuned MobileNet Convolutional Neural Network is developed to detect and classify strawberry and cherry fruit types in the outdoor field. The proposed CNN model is trained on 4250 strawberry fruit images, 3878 Cherry fruit images … …Journal of Computer Science, Vol. 17, Issue 1 · 20 Jan 2021 · 7,953 accessesView PDFCite
Research ArticleOpen accessIn the abstractSkin Images SegmentationAli El-ZaartProblem statement: Image segmentation is a fundamental step in many applications of image processing. Skin cancer has been the most common of all new cancers detected each year. At early stage detection of skin cancer, simple and economic treatment can cure it mostly. An accurate segmentation of skin images can help the diagnosis to define well the region of the … …Journal of Computer Science, Vol. 6, Issue 2 · 28 Jul 2010 · 7,023 accessesView PDFCite
Research ArticleOpen accessIn the abstractImproved Statistical Speech Segmentation Using Connectionist ApproachM. S. Salam, Dzulkifli Mohamad, S. H. SallehProblem statement: Speech segmentation is an important part for speech recognition, synthesizing and coding. Statistical based approach detects segmentation points via computing spectral distortion of the signal without prior knowledge of the acoustic information proved to be able to give good match, less omission but lot of insertion. These insertion points dropped segmentation accuracy. Approach: This study proposed a fusion … …Journal of Computer Science, Vol. 5, Issue 4 · 30 Apr 2009 · 7,680 accessesView PDFCite
Research ArticleOpen accessIn the abstractAdaptive Control of Robotic Manipulators with Improvement of the Transient Behavior Through an Intelligent Supervision of the Free-Design Parameters and the Sampling PeriodM. De La Sen, A. Almansa, J.C. SotoAn adaptive control scheme for mechanical manipulators proposed. The control loop consists of a network for learning the robot's inverse dynamics and on-line generating the control signal. Some simulation results were provided to evaluate the design. A supervisor was used to improve the performances of the system during the adaptation transients. The supervisor exerts two supervisory actions. The first one … …American Journal of Applied Sciences, Vol. 4, Issue 6 · 30 Jun 2007 · 6,881 accessesView PDFCite