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41 results for “Support Vector Machines (SVM)”
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Research ArticleOpen accessIn the abstractA Novel SIFT-SVM Approach for Prostate Cancer DetectionSwetha Parvatha Reddy Chandrasekhara, Mohan Govindsa Kabadi, SrivinayProstate cancer is a major cause of concern in male population as it is said to affect 1 in every 7 men in their lifetime. The number of cases being registered for prostate cancer and its mortality rates are increasing yearly at an alarming rate. Due to the high resolution and multi-dimensionality of the Magnetic Resonance Imaging (MRI) images, proper … …Journal of Computer Science, Vol. 16, Issue 12 · 22 Dec 2020 · 7,530 accessesView PDFCite
Research ArticleOpen accessIn the abstractMissing Values Treatment and Feature Reduction Analysis to Enhance ClassificationD. Muralidharan, K. Renuka, Mulagala Jaswant et al.Datasets may have large number of features which makes it hard and time consuming to classify. Additionally, they may have irrelevant and noise features too with missing values. The missing values should be treated in a proper way so that the classifier accuracy can be improved. There is also a need to reduce features and select only the features necessary … …Journal of Computer Science, Vol. 16, Issue 2 · 20 Feb 2020 · 8,119 accessesView PDFCite
Review ArticleOpen accessIn the abstractProtein Sequences Features Extraction for Predicting Beta- Turns and their Types: A ReviewMurtada Khalafallah Elbashir ElfakiBeta-turns are considered to be important secondary structure types that have essential role in molecular recognition, protein folding and stability. They represent 25% of protein structures, therefore they are the most common type of non-repetitive or tight turns structures. Their prediction is considered to be an important issue in bioinformatics and molecular biology, because it provides valuable information and inputs … …Journal of Computer Science, Vol. 15, Issue 9 · 1 Oct 2019 · 7,701 accessesView PDFCite
Research ArticleOpen accessIn the abstractComparison of Classification Techniques on Fused Optical and SAR Images for Shoreline Extraction: A Case Study at Northeast Coast of Peninsular MalaysiaSyaifulnizam Abd Manaf, Norwati Mustapha, Md Nasir Sulaiman et al.Shoreline is a very important element to identify exact boundary at the coastal areas of a country. However, in order to identify land-water boundary for a large region using traditional ground survey technique is very time consuming. Alternatively, shoreline can be extracted by using satellite images that minimizes the mapping errors. The trend of extracting shoreline has been shifted from … …Journal of Computer Science, Vol. 12, Issue 8 · 27 Oct 2016 · 7,713 accessesView PDFCite
Research ArticleOpen accessIn the abstractDAILY CRUDE OIL PRICE FORECASTING MODEL USING ARIMA, GENERALIZED AUTOREGRESSIVE CONDITIONAL HETEROSCEDASTIC AND SUPPORT VECTOR MACHINESRana Abdullah Ahmed, Ani Bin ShabriCrude oil price forecasting is gaining increased interest globally. This interest is due mainly to the economic value attached to the product. For this reason, new forecasting methods are proposed in the literature. This paper proposes a novel technique for forecasting crude oil price based on Support Vector Machines (SVM). The study adopts the data on crude oil price of … …American Journal of Applied Sciences, Vol. 11, Issue 3 · 11 Jan 2014 · 8,734 accessesView PDFCite
Research ArticleOpen accessIn the abstractSPEECH/MUSIC CLASSIFICATION USING WAVELET BASED FEATURE EXTRACTION TECHNIQUESThiruvengatanadhan Ramalingam, P. DhanalakshmiAudio classification serves as the fundamental step towards the rapid growth in audio data volume. Due to the increasing size of the multimedia sources speech and music classification is one of the most important issues for multimedia information retrieval. In this work a speech/music discrimination system is developed which utilizes the Discrete Wavelet Transform (DWT) as the acoustic feature. Multi … …Journal of Computer Science, Vol. 10, Issue 1 · 8 Nov 2013 · 6,846 accessesView PDFCite
Research ArticleOpen accessIn the abstractIMPROVING INDEPENDENT COMPONENT ANALYSIS USING SUPPORT VECTOR MACHINES FOR MULTIMODAL IMAGE FUSIOND. Egfin Nirmala, A. Bibin Sam Paul, V. VaidehiThe objective of this study is to combine multiple images of a scene acquired by different sensors to create a new image with all important information from the input images. Recent studies show that bases trained using Independent Component Analysis (ICA) is effective in multisensor fusion and has improved performance over traditional wavelet approaches. In the ICA based fusion, the … …Journal of Computer Science, Vol. 9, Issue 9 · 6 Aug 2013 · 7,277 accessesView PDFCite
Research ArticleOpen accessIn the abstractPoetry Classification Using Support Vector MachinesShahrul Azman Noah, Noraini Jamal, Masnizah MohdProblem statement: Traditional Malay poetry called pantun is a form of art to express ideas, emotions and feelings in the form of rhyming lines. Malay poetry usually has a broad and deep meaning making it difficult to be interpreted. Moreover, few efforts have been done on automatic classification of literary text such as poetry. Approach: This research concerns with the … …Journal of Computer Science, Vol. 8, Issue 9 · 8 Aug 2012 · 8,874 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Novel Local Network Intrusion Detection System Based on Support Vector MachineMuamer N. Mohammad, Norrozila Sulaiman, Emad T. KhalafProblem statement: Past few years have witnessed a growing recognition of intelligent techniques for the construction of efficient and reliable Intrusion Detection Systems (IDS). Many methods and techniques were used for modeling the IDS, but some of them contribute little or not to resolve it. Approach: Intrusion detection system for local area network by using Support Vector Machines (SVM) was … …Journal of Computer Science, Vol. 7, Issue 10 · 6 Aug 2011 · 7,318 accessesView PDFCite
Research ArticleOpen accessIn the abstractFeature Subset Selection for Hot Method Prediction using Genetic Algorithm wrapped with Support Vector MachinesSandra Johnson, Valli ShanmugamProblem statement: All compilers have simple profiling-based heuristics to identify and predict program hot methods and also to make optimization decisions. The major challenge in the profile-based optimization is addressing the problem of overhead. The aim of this work is to perform feature subset selection using Genetic Algorithms (GA) to improve and refine the machine learnt static hot method predictive … …Journal of Computer Science, Vol. 7, Issue 5 · 7 May 2011 · 7,238 accessesView PDFCite