image colorization has always been a hot topic in computer vision. Since the emergence of deep learning and its excellent performance in many image-processing tasks, image colorization methods based on convolutional n...
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This paper uses traditional algorithms and deep learning algorithms to recover datacube obtained by CASSI and CSIMS in order to verify that CSIMS outperforms CASSI by comparing the Peak Signal to Noise Ratio (PSNR), S...
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ISBN:
(纸本)9781510672413;9781510672406
This paper uses traditional algorithms and deep learning algorithms to recover datacube obtained by CASSI and CSIMS in order to verify that CSIMS outperforms CASSI by comparing the Peak Signal to Noise Ratio (PSNR), Structural Similarity (SSIM) and Relative spectral Quadratic Error (RQE) of the reconstructed datacube. The experimental results show that the datacube of CASSI and CSIMS can be both reconstructed by ADMM- TV algorithm which is the most effective among the traditional algorithms. PSNR of the reconstructed datacube of CASSI is 32.50 dB, while that of CSIMS is 35.53 dB, with an increase of 3.03 dB. By using deep learning algorithm, both systems improve substantially under the PnP-HSI network, with PSNR of CASSI growing to 38.85 dB and that of CSIMS growing to 41.97 dB, which can be seen that CSIMS is still 3.12 dB higher than CASSI.
The Pacific Northwest National Laboratory (PNNL) has recently developed a next-generation cylindrical millimeter-wave imaging system. This system is based on linear sparse multistatic imaging arrays. Data from this sy...
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ISBN:
(纸本)9781510674158;9781510674141
The Pacific Northwest National Laboratory (PNNL) has recently developed a next-generation cylindrical millimeter-wave imaging system. This system is based on linear sparse multistatic imaging arrays. Data from this system can be focused using 3D FFT-based reconstruction algorithms, which are reasonably efficient and can be performed in near real time, or by back-projection methods that are versatile and more accurate but are computationally intensive and require lengthy post-processing. Cylindrical Fast Backprojection (CFBP) is a novel image reconstruction algorithm developed at PNNL that radically increases the efficiency of backprojection and is ideally suited to microwave and millimeter-wave imaging systems based on scanned linear arrays such as body scanners in common use for aviation security screening. This method achieves its gains in efficiency by separating a full backprojection into a sequence of three steps, range focusing, vertical focusing, and lateral focusing, with intermediate results used to avoid repetitive multidimensional computation. The method is called cylindrical fast backprojection due to the use of two-dimensional stored results, or look-up tables, that have cylindrical symmetry about the linear array. The method is well suited to cylindrically scanned linear arrays but is equally valid for linear arrays scanned to form planar or arbitrary apertures. This paper describes the CFBP algorithm and validates its performance using simulated data.
The Smart Medical Box is a sophisticated IoT-driven solution designed to enhance medication adherence by utilizing computer vision and machine learning. The system automates the identification and extraction of essent...
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To safeguard the operation of ultra-high voltage transmission lines, this study introduces a technique for dynamically monitoring potential security threats to these lines. This technique integrates images and point c...
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Dermoscopy, an epiluminescence light microscope that magnifies lesions and enables investigation down to the dermo-epidermal interface, is a non-invasive method that doctors may use to help with the diagnosis of melan...
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Deep Learning has shown great potential in developing applications capable of automatically generating captions or descriptions for images and video frames. The critical components of this process are imageprocessing...
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Security of data becomes more and more important each day. The importance is even more pronounced if the data contain sensitive information, such as those shown in medical images. There are already several solutions t...
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In recent years Human Object Interaction (HOI) detection has experienced rapid performance growth mainly due to the development of various deep learning-based methods and algorithms. One of the most popular approaches...
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An aberrant mass of rapidly proliferating brain cells, known as a brain tumour, may develop into various forms of cancer. The segmentation of brain tumours by MRI scans is a challenging but crucial process with severa...
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