Dabrowski / Rahman / Paul Image and Video Technology

PSIVT 2019 International Workshops, Sydney, NSW, Australia, November 18–22, 2019, Revised Selected Papers
Erscheinungsjahr 2020
ISBN: 978-3-030-39770-8
Verlag: Springer International Publishing
Format: PDF
Kopierschutz: 1 - PDF Watermark

E-Book, Englisch, Band 11994, 207 Seiten, eBook

Reihe: Lecture Notes in Computer Science

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, and Solutions in the Areas of Computer Vision; Workshop on Passive and Active Electro-Optical Sensors for Aerial and Space Imaging; Workshop on Deep Learning and Image Processing Techniques for Medical Images; and Workshop on Deep Learning for Video and Image Analysis. The 16 revised full papers presented were carefully selected from 26 submissions. The papers cover the full range of state-of-the-art research in image and video technology with topics ranging from well-established areas to novel current trends.

Zielgruppe

Research

Autoren/Hrsg.

Dabrowski, Joel Janek

Rahman, Ashfaqur

Paul, Manoranjan

Inhaltsverzeichnis

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.