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Titlebook: Advances in Computational Intelligence Techniques; Shruti Jain,Meenakshi Sood,Sudip Paul Book 2020 Springer Nature Singapore Pte Ltd. 2020

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期刊全称Advances in Computational Intelligence Techniques
影响因子2023Shruti Jain,Meenakshi Sood,Sudip Paul
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发行地址Examines a variety of computational techniques applied in signal analysis and medical image analysis.Discusses the latest soft computing techniques and their applications in various engineering fields
学科分类Algorithms for Intelligent Systems
图书封面Titlebook: Advances in Computational Intelligence Techniques;  Shruti Jain,Meenakshi Sood,Sudip Paul Book 2020 Springer Nature Singapore Pte Ltd. 2020
影响因子.This book highlights recent advances in computational intelligence for signal processing, computing, imaging, artificial intelligence, and their applications. It offers support for researchers involved in designing decision support systems to promote the societal acceptance of ambient intelligence, and presents the latest research on diverse topics in intelligence technologies with the goal of advancing knowledge and applications in this rapidly evolving field. As such, it offers a valuable resource for researchers, developers and educators whose work involves recent advances and emerging technologies in computational intelligence..
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BN for Reinforced Concrete Structures,mation of the input image. The proposed architecture predicts the probability of an image being glaucoma. The model has been experimented with Refugee and Drishti datasets. Our proposed model is able to diagnose the glaucoma disease automatically with an accuracy of 90%, sensitivity of 96%, and specificity of 84%, respectively.
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Financial Governance on the Cloudcolor (red, green and blue) filters are applied on the image for better results. The blur kernel is deconvolved out of the blurred image to obtain a sharp image. This approach is better than the baseline approach of using Richardson–Lucy algorithm.
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Successes and Limitations of Inflation,pared against the standard algorithms, i.e. delay and sum (DAS) beamformer as well as recurrent neural network (RNN) model and from that it has been observed that SVM-based DOA estimation outperforms DAS beamformer in all cases and has better performance than RNN model for low values of signal-to-noise ratio (SNR).
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