Buch, Englisch, Band 350, 578 Seiten, Format (B × H): 155 mm x 235 mm, Gewicht: 890 g
16th EAI International Conference, CollaborateCom 2020, Shanghai, China, October 16-18, 2020, Proceedings, Part II
Buch, Englisch, Band 350, 578 Seiten, Format (B × H): 155 mm x 235 mm, Gewicht: 890 g
ISBN: 978-3-030-67539-4
Verlag: Springer International Publishing
The 61 full papers and 16 short papers presented were carefully reviewed and selected from 211 submissions. The papers reflect the conference sessions as follows: Collaborative Applications for Network and E-Commerce; Optimization for Collaborate System; Cloud and Edge Computing; Artificial Intelligence; AI Application and Optimization; Classification and Recommendation; Internet of Things; Collaborative Robotics and Autonomous Systems; Smart Transportation.
Zielgruppe
Research
Autoren/Hrsg.
Weitere Infos & Material
Artificial Intelligence.- AI Application and Optimization.- Classification and Recommendation.- Internet of Things.- Collaborative Robotics and Autonomous Systems.- Smart Transportation.- Self-organised Flocking with Simulated Homogeneous Robotic Swarm.- Investigation of Cue-based Aggregation Behaviour in Complex Environments.- Towards Efficient and Privacy-Preserving Service QoS.- Prediction with Federated Learning.- A Reinforcement Learning based Approach to Identify Resource Bottlenecks for Multiple Services Interactions in Cloud Computing Environments.- Differentially Private Location Protection with Staircase Mechanism under Temporal Correlations.- Resource Management.- Mobile Edge Server Placement Based on Bionic Swarm Intelligent Optimization Algorithm.- A MOEAD-based Approach to Solving the Staff Scheduling Problem.- A deep reinforcement learning based resource autonomic provisioning approach for cloud services.- End-to-end QoS Aggregation and Container Allocation for Complex Microservice Flows.- A DQN-based Approach for Online Service Placement in Mobile Edge Computing.- A Hybrid Collaborative Virtual Environment with Heterogeneous Representations for Architectural Planning.- Smart Transportation.- T2I-CycleGAN: A CycleGAN for Maritime Road Network Extraction from Crowdsourcing Spatio-Temporal AIS Trajectory Data.- Where is the Next Path? A Deep Learning Approach to Path Prediction without Prior Road Networks HMM-based Traffic State Prediction And Adaptive Routing Method In VANETs.- A Hybrid Deep Learning Approach for Traffic Flow Prediction in Highway Domain.- HomoNet: Unified License Plate Detection andRecognition in Complex Scenes.
