Del 11994 i serien Lecture Notes in Computer Science

Image and Video Technology

PSIVT 2019 International Workshops, Sydney, NSW, Australia, November 18–22, 2019, Revised Selected Papers

Häftad, Engelska, 2020

AvJoel Janek Dabrowski,Ashfaqur Rahman,Manoranjan Paul

719 kr

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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;

Produktinformation

Utgivningsdatum2020-01-27
Mått155 x 235 x 13 mm
Vikt341 g
FormatHäftad
SpråkEngelska
SerieLecture Notes in Computer Science
Antal sidor207
FörlagSpringer Nature Switzerland AG
ISBN9783030397692

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Systemvetenskap och AI inom Data och IT
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Nätverk och kommunikation inom Data och IT

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.