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    Compressed Sensing Based Apple Image Measurement Matrix Selection by Ying Xiao, Wanlin Gao, Ganghong Zhang, Han Zhang

    Published 2015-07-01
    “…The purpose of this paper is to design a measurement matrix of apple image based on compressed sensing to realize low cost sampling apple image. …”
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    Determination of Knitted Fabric Porosity Using Digital Imaging Techniques by Manoj Kumar Imrith, Roshan Unmar, Satyadev Rosunee

    Published 2016-01-01
    “…This paper has investigated the porosity of knitted fabrics using digital imaging techniques. A number of different methods have been proposed to determine the porosity of knitted fabrics, which include digital imaging, geometrical modeling, and air permeability. …”
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  5. 765

    Model-Corrected Microwave Imaging through Periodic Wall Structures by Paul C. Chang, Robert J. Burkholder, John L. Volakis

    Published 2012-01-01
    “…A model-based imaging framework is applied to correct the target distortion seen in microwave imaging through a periodic wall structure. …”
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    Image Restoration Based on the Hybrid Total-Variation-Type Model by Baoli Shi, Zhi-Feng Pang, Yu-Fei Yang

    Published 2012-01-01
    “…We propose a hybrid total-variation-type model for the image restoration problem based on combining advantages of the ROF model with the LLT model. …”
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    An Adaboost-Backpropagation Neural Network for Automated Image Sentiment Classification by Jianfang Cao, Junjie Chen, Haifang Li

    Published 2014-01-01
    “…The development of multimedia technology and the popularisation of image capture devices have resulted in the rapid growth of digital images. …”
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    An affine invariant approach for dense wide baseline image matching by Fanhuai Shi, Jian Gao, Xixia Huang

    Published 2016-12-01
    “…Visual sensor networks have emerged as an important class of sensor-based distributed intelligent systems, where image matching is one of the key technologies. This article presents an affine invariant method to produce dense correspondences between uncalibrated wide baseline images. …”
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