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119 results for “Support Vector Machine/SVM”
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Research ArticleOpen accessIn the keywordsSRBIR: Semantic Region Based Image Retrieval by Extracting the Dominant Region and Semantic LearningI. Felci Rajam, S. ValliProblem statement: The Semantic Region Based Image Retrieval (SRBIR) system that automatically segments the dominant foreground region, consisting of the semantic concept of the image, such as elephants, roses and does the semantic learning, is proposed. Approach: The system segments an image into different regions and finds the dominant foreground region in it, which is the semantic concept of that … …Journal of Computer Science, Vol. 7, Issue 3 · 7 Mar 2011 · 7,026 accessesView PDFCite
Research ArticleOpen accessIn the keywordsA Computer Aided Diagnosis System for Lung Cancer Detection\Using Support Vector MachineM. Gomathi, P. ThangarajProblem statement: Computer Tomography (CT) has been considered as the most sensitive imaging technique for early detection of lung cancer. Approach: On the other hand, there is a requirement for automated methodology to make use of large amount of data obtained CT images. Computer Aided Diagnosis (CAD) can be used efficiently for early detection of Lung Cancer. Results: The usage … …American Journal of Applied Sciences, Vol. 7, Issue 12 · 31 Dec 2010 · 8,285 accessesView PDFCite
Research ArticleOpen accessIn the keywordsEfficient Detection of Palm and Hand Landmark for Speech Impaired People Using Mediapipe ModelSharmila Rathod, Nilesh Rathod, Nilesh Marathe et al.Human-machine interaction may be a basic figure in this age of touch-screen gadgets. Numerous gadgets are being created that can be worked without touching the system. So, in this consideration, how to function the framework utilizing signals instead of touching it appears. The point of this study is to create different communication procedures between humans and individual computers that would … …Journal of Computer Science, Vol. 20, Issue 9 · 24 Jun 2024 · 5,415 accessesView PDFCite
Research ArticleOpen accessIn the keywordsSoft Marking Scheme of SVM Hierarchical Classifiers for Attack ClassificationAzizi Abdullah, Warhamni Jani@MokhtarClassification is a predictive modelling problem that involves assigning a class label to an instance correctly. There exist several strategies in machine learning to deal with the multi-class classification problems for attack detection. One of the popular strategies is the one-vs-one that decomposes the multi-class problem into multiple binary ones. The approach has been applied in many popular supervised learning … …Journal of Computer Science, Vol. 17, Issue 9 · 27 Sep 2021 · 6,000 accessesView PDFCite
Research ArticleOpen accessIn the keywordsSPEECH/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 · 6,841 accessesView PDFCite
Research ArticleOpen accessIn the keywordsWavelet Statistical Texture Features with Orthogonal Operators Tumour Classification in Magnetic Resonance Imaging BrainR. Meenakshi, P. AnandhakumarTumors medically also called neoplasms are an abnormal mass of tissue resulting from uncontrolled proliferation or division of cells occurring in the human body. If such growth is located in the brain then it is called as brain tumor. Identification of such tumors is a major challenge in the field of medical science. Early identification of tumors prove to be … …American Journal of Applied Sciences, Vol. 10, Issue 10 · 5 Sep 2013 · 6,600 accessesView PDFCite
Research ArticleOpen accessIn the keywordsCategorizer Agent for Electronic Computer Science Academic PapersKhalifa Chekima, Patricia AnthonyProblem statement: With the rapid development of World Wide Web (WWW), a huge amount of information is now accessible to the web users. This phenomenon has attracted academic users to publish their research papers online, at the same time downloading and sharing academic papers among them through WWW. Categorizing a document manually can take up considerable amount of user’s time … …American Journal of Economics and Business Administration, Vol. 3, Issue 1 · 31 Jan 2011 · 7,861 accessesView PDFCite
Research ArticleOpen accessIn the abstractPandemic Analysis and Preparedness Using a Three Layer Machine Learning ApproachArtika Singh, Manisha JailiaOutbreak analysis provides research-based information and data to enable scientific decision-making to manage an effective response to a pandemic. Pandemic analysis has its own set of challenges, such as limited data, the need for real time analysis, and the complexity of outbreak patterns. This study proposes a hybrid approach to manage such a spread through a 3-layer machine learning-based outbreak … …Journal of Computer Science, Vol. 22, Issue 11 · 15 Oct 2026 · 614 accessesView PDFCite
Research ArticleOpen accessIn the abstractAssessing Supervised Classification Algorithms for Mangrove Detection and Differentiation from Other Forest Types in Paiton District, Probolinggo RegencyKaruniawan Puji Wicaksono, Fathor Rohman, Yasushi MitsudaRemote sensing provides an effective approach for monitoring forest cover dynamics, yet distinguishing mangroves from other forest types remains challenging in heterogeneous coastal landscapes. This study compares six supervised classification algorithms: Linear Discriminant Analysis (LDA), Quadratic Discriminant Analysis (QDA), Mixture Discriminant Analysis (MDA), Support Vector Machine (SVM), Random Forest (RF), and eXtreme Gradient Boosting (XGBoost) for mangrove detection in Paiton, … …OnLine Journal of Biological Sciences, Vol. 26, Issue 3 · 1 Sep 2026 · 844 accessesView PDFCite
Research ArticleOpen accessIn the abstractEpsilon-Insensitive Primal Loss With Support Vector Machine for Robust Cotton Leaf Disease ClassificationPavana Kumar Eramachetty Dhanajayalu, Malathi Sivasamy, Chitveli Siva Balaji YadavCotton diseases significantly reduce both yield and quality of crops, making early and accurate identification of the disease crucial for effective prevention and control. However, achieving a balance between lightweight models and precise classification of cotton diseases remains challenging. This difficulty arises primarily from the dispersed nature of disease symptoms and interference from noisy backgrounds, which complicate the detection process. … …Journal of Computer Science, Vol. 22, Issue 6 · 5 Aug 2026 · 755 accessesView PDFCite