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Titlebook: Cognitive Internet of Things: Frameworks, Tools and Applications; Huimin Lu Book 2020 Springer Nature Switzerland AG 2020 Computational In

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Medicine Discrimination of NIRS Based on Regularized Collaborative Representation Classification wi and more important. Then near-infrared spectroscopy (NIRS) is a popular and effective technique used on the medicine classification with nondestructive characteristics. To solve the discrimination of medicines, the sparse signal representation model is established in the presence of spectrum crosso
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Multi-objective Bird Swarm Algorithm,ated sorting approach and parallel coordinates. A developed algorithm, known as multi-objective BSA (MOBSA) is proposed. When the external archive for non-dominated solutions is full to overflowing, the solution with greatest density would be rejected. The approaches were tested and compared on benc
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Performance Modeling of Spark Computing Platform,een proposed. Spark is the newer solution of the universal parallel framework which like Hadoop MapReduce. Compare the Hadoop, Spark’s performance has been increased significantly. As a data analysis framework, researchers are particularly concerned about its performance. So in this paper, we use a
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An Improved Unsupervised Band Selection of Hyperspectral Images Based on Sparse Representation, tremendous applications as well as many problems such as the curse of dimensionality. Band selection is an effective method to reduce the spectral dimension which is one of popular topics in hyperspectral remote sensing. Motivated by previous sparse representation method, we present a novel framewo
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Nuclear Norm Regularized Structural Orthogonal Procrustes Regression for Face Hallucination with Poations, thus the learned representations are not beneficial for the following reconstruction. In this paper, we propose a nuclear norm regularized structural orthogonal Procrustes regression (N2SOPR) method to learn pose-robust feature representations for efficient face hallucination. The orthogonal
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Salt and Pepper Noise Suppression for Medical Image by Using Non-local Homogenous Information,l and anti-packing model (NAM). The NAM could divide the image into several homogenous blocks and it is sensitive to the additive extra energy. Thus the noise could be detected effectively due to the usage of bit-plane during the division. Then corrupted points are estimated by using a distance base
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1860-949X ligence and Robotics 2018 (ISAIR2018), held in Nanjing, ChinThis book provides insights into the research in the fields of artificial intelligence in combination with Internet of Things (IoT) technologies. Today, the integration of artificial intelligence and IoT technologies is attracting considera
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