Image and video technology : PSIVT 2019 International Workshops, Sydney, NSW, Australia, November 18-22, 2019, revised selected papers / Joel Janek Dabrowski, Ashfaqur Rahman, Manoranjan Paul (eds.).

This book constitutes the thoroughly refereed post-conference proceedings of four international workshops held in the framework of the 9th Pacific-Rim Symposium on Image and Video Technology, PSIVT 2019, in Sydney, NSW, Australia, in November 2019: Vision-Tech: Workshop on Challenges, Technology, an...

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Bibliographic Details
Corporate Author: PSIVT (Symposium) Sydney, N.S.W.)
Other Authors: Dabrowski, Joel Janek, Rahman, Ashfaqur, Paul, Manoranjan
Format: eBook
Language:English
Published: Cham : Springer, 2020.
Series:Lecture notes in computer science ; 11994.
LNCS sublibrary. Image processing, computer vision, pattern recognition, and graphics.
Subjects:
Online Access:Click for online access
Table of Contents:
  • Rain Streak Removal with Well-Recovered Moving Objects From Video Sequences Using Photometric Correlation
  • Face Analysis: State of the Art and Ethical Challenges
  • Location Analysis Based Waiting Time Optimization
  • In-Orbit Geometric Calibration of Firebird's Infrared Line Cameras
  • Evaluation of Structures and Methods for Resolution Determination of Remote Sensing Sensors
  • 3D Image Reconstruction from Multi-focus Microscopic Images
  • Block-Wise Authentication and Recovery Scheme for Medical Images Focusing on Content Complexity
  • GAN-based Method for Synthesizing Multi-Focus Cell Images
  • Improving Image-Based Localization with Deep Learning: The Impact of the Loss Function
  • Face-based Age and Gender Classification using Deep Learning Model
  • SO-Net: Joint Semantic Segmentation and Obstacle Detection using Deep Fusion of Monocular Camera and Radar
  • Deep Forest Approach for Facial Expression Recognition
  • Weed Density Estimation Using Semantic Segmentation
  • Detecting Global Exam Events in Invigilation Videos using 3D CNN
  • Spatial Hierarchical Analysis Deep Neural Network for RGBD Object Recognition
  • Reading Digital Video Clocks by Two Phases of Connected Deep Networks.