The Proceedings of the International Conference on Sensing and Imaging (eBook, PDF)

Redaktion: Jiang, Ming; Quinto, Eric Todd; Louis, Alfred K.; Ida, Nathan

• Format: PDF

Produktbeschreibung

This book collects ¿a number of papers presented at the International Conference on Sensing and Imaging, which was held at Chengdu University of Information Technology on June 5-7, 2017. Sensing and imaging is an interdisciplinary field covering a variety of sciences and techniques such as optics, electricity, magnetism, heat, sound, mathematics, and computing technology. The field has diverse applications of interest such as sensing techniques, imaging, and image processing techniques. This book will appeal to professionals and researchers within the field.

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Produktdetails

• Verlag: Springer International Publishing
• Seitenzahl: 430
• Erscheinungstermin: 18. September 2018
• Englisch
• ISBN-13: 9783319916590
• Artikelnr.: 56819869

Inhaltsangabe

Chapter1: Sensing and Actuation: A Case for Multidisciplinary Engineering Education.- Chapter2: Advances in Reconstruction Algorithms for Diffuse Correlation Spectroscopy and Tomography.- Chapter3: Steady and Transient Flow CFD Simulations in an Aorta Model of Normal and Aortic Aneurysm Subjects.- Chapter4: Blur-Specific No-Reference Image Quality Assessment: A Classification and Review of Representative Methods.- Chapter5: Intensity Inhomogeneity Quantization based Variational Model for Segmentation of Hepatocellular Carcinoma (HCC) in Computed Tomography (CT) Images.- Chapter6: A novel computed tomography scanning mode and local image reconstruction of impurities in pipeline.- Chapter7: A Linearity Bootstrapped Switch with Dynamic Bulk Biasing Design for CMOS Image Sensors.- Chapter8: A Low-Complexity Bound Estimation Technique for Maximum Likelihood Receivers.- Chapter9: Analysis of RF Channel Isolation Impactin Wireless Co-time Co-frequency Full Duplex.- Chapter10: Application of a dual motor synchronous servo control system to the photoelectronic detection system.- Chapter11: Calibrating TOF Sensor by Fusing Normal Maps.- Chapter12: Flame Temperature Sensor Based on a Silicon Nitride Hot Surface Igniter.- Chapter13: Analytical Calculation of Induced Voltages of Uniform Eddy Current Probes above a Moving Conductor.- Chapter14: An Enhanced Unscented Kalman Filter Method based on the Covariance Intersection Algorithm.- Chapter15: Application in Image Denoising using Fractional Total Variation Theory.- Chapter16: Total Variation with Overlapping Group 2 Sparsity for Removing Mixed Noise.- Chapter17: Image restoration for target behind inhomogeneous turbid medium via longitudinal laser tomography.- Chapter18: A hybrid approach for object proposal generation.- Chapter19: Adaptive-order Regression-based MR Image Super-resolution.-Chapter20: A Cone-Beam CT Reconstruction Algorithm Constrained by Non-local Prior from Sparse-View Data.- Chapter21: Robust binary keypoint descriptor based on local hierarchical octagon pattern.- Chapter22: Seamless mosaicking of multi-strip airborne hyperspectral images based on Hapke model.- Chapter23: Computational Calibration and Correction for Gigapixel Imaging System.- Chapter24: Expected Value Correction Based Computed Tomography for Airplane Engine.- Chapter25: Low-dose CT post-processing based on 2D residual network.- Chapter26: Phase Congruency and Its Application to Tubular Structure Extraction.- Chapter27: Non-rigid 3D CT/MR Liver Registration with Discontinuous Transforms using Total Variation Regularization.- Chapter28: Directional diffusion filter bank and texture quality measurement for robust orientation estimation and enhancement of fingerprint images.- Chapter29: Optimization of Event Processingin RFID Enabled Healthcare.- Chapter30: Measurement of the Gas-solid Flow in a Wurster Tube Using 3D Electrical Capacitance Tomog-raphy Sensor.- Chapter31: Investigation the application of electrical capacitance tomography on pipe flow with thick wall.- Chapter32: A New Method for Differential Phase Contrast Imaging without Phase Stepping.- Chapter33: Automatic Liver Tumor Segmentation Based on Random Forest and Fuzzy Clustering.- Chapter34: Using Electrically Tunable Lens to Improve Axial Resolution and Imaging Field in Light Sheet Fluorescence Microscope.