Advances in Computer Vision Proceedings of the 2019 Computer Vision Conference (CVC), Volume 2
Titre:
Advances in Computer Vision Proceedings of the 2019 Computer Vision Conference (CVC), Volume 2
ISBN (Numéro international normalisé des livres):
9783030177980
Edition:
1st ed. 2020.
PRODUCTION_INFO:
Cham : Springer International Publishing : Imprint: Springer, 2020.
Description physique:
XII, 767 p. 638 illus., 312 illus. in color. online resource.
Collections:
Advances in Intelligent Systems and Computing, 944
Table des matières:
Data-Driven Multi-step Demand Prediction for Ride-hailing Services using Convolutional Neural Network -- Proactive Management of Regulatory Policy Ripple Effects Via Computational Hierarchical Change Management Structure -- Iceberg Detection by CNN based on Incidence-Angle Confusion -- The Effectiveness of Distinctive Information for Cancer Cell Analysis through Big Data -- Forecasting Food Sales in a Multiplex using Dynamic Artificial Neural Networks -- Cooperation of Virtual Reality and Real Objects with HoloLens -- Feature Map Transformation for Multi-Sensor Fusion in Object Detection Networks for Autonomous Driving -- Application of Remote Sensing for Automated Litter Detection and Management -- Robots in Healthcare: A Survey -- Character Localization based on Support Vector Machine.
Extrait:
This book presents a remarkable collection of chapters covering a wide range of topics in the areas of Computer Vision, both from theoretical and application perspectives. It gathers the proceedings of the Computer Vision Conference (CVC 2019), held in Las Vegas, USA from May 2 to 3, 2019. The conference attracted a total of 371 submissions from pioneering researchers, scientists, industrial engineers, and students all around the world. These submissions underwent a double-blind peer review process, after which 120 (including 7 poster papers) were selected for inclusion in these proceedings. The book's goal is to reflect the intellectual breadth and depth of current research on computer vision, from classical to intelligent scope. Accordingly, its respective chapters address state-of-the-art intelligent methods and techniques for solving real-world problems, while also outlining future research directions. Topic areas covered include Machine Vision and Learning, Data Science, Image Processing, Deep Learning, and Computer Vision Applications.
Auteur collectif ajouté:
Langue:
Anglais