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4 articles for “SVM RBF”
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Brain Tumor Detection
Abstract: The MRI, or magnetic resonance imaging, is one of the most common practices in detecting a brain tumor since it contains important information used to extensively scan the human brain’s internal anatomy. The treatment of any tumor depends entirely on the knowledge and expertise of the physician. This paper reflects the identification of brain tumors using different machine learning algorithms along with the convolution neural network (CNN) and transfer learning. …
Published in Research & Reviews: A Journal of Bioinformatics · Vol. 8, Issue 1, 2021 · pp. 45–52 Read article
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Soft Computing Based Prediction of Deviator Stress of Waste Plastic Reinforced Sand
Abstract: In the recent past, the soft computing techniques have received a significant attention for solution of the geotechnical stability problems. Following the trend, the present study tries to explore the use of different soft computing techniques such as random forest regression, support vector machines (SVM) RBF kernel, SVM poly kernel and M5P model tree for the prediction of deviator stress of sand reinforced with waste plastic strips. The deviator stress …
Published in Journal of Geotechnical Engineering · Vol. 6, Issue 3, 2019 · pp. 1–7 Read article
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Unsupervised Learning Techniques in Neural Network for Face Recognition
Abstract: This paper represents the review of systematic comparison between of unsupervised learning algorithms for face recognition. In neural network, different algorithms are used for face recognition. Each algorithm has different accuracy factors. Commonly these methods asset a set of base images and serve faces as linear combo of images. In our proposed review, firstly we discuss about the face detection using neural network along with the concept of digital image …
Published in Journal of Advancements in Robotics · Vol. 7, Issue 1, 2020 · pp. 25–29 Read article
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Citizen Opinion Mining Initiatives in Government Decision Making by Categorizing Citizen Sentiments
Abstract: AbstractCitizen opinion mining (C.O.M.) is a type of natural language processing (NLP) for finding the sentiments of citizen on various targeted government policies. Opinion mining techniques can be used for measuring influence facts like citizen behavior, desire, needs that help to improve government services. It includes building a system to gather and examine opinions for specific policy, made in weblog posts, comments, stories or tweets. Proposed approach gives brief description …
Published in Current Trends in Information Technology · Vol. 7, Issue 2, 2017 · pp. 1–10 Read article