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Edge-computing

Deep Learning on EDGE devices

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Showing 301–325 of 1279 papers

TitleStatusHype
CoRaiS: Lightweight Real-Time Scheduler for Multi-Edge Cooperative Computing—0
Coordination-free Decentralised Federated Learning on Complex Networks: Overcoming Heterogeneity—0
A Fast Edge-Based Synchronizer for Tasks in Real-Time Artificial Intelligence Applications—0
Cooperative Task Offloading and Block Mining in Blockchain-based Edge Computing with Multi-agent Deep Reinforcement Learning—0
Architectural Blueprint For Heterogeneity-Resilient Federated Learning—0
A Cost-Efficient FPGA Implementation of Tiny Transformer Model using Neural ODE—0
A 5G Enabled Adaptive Computing Workflow for Greener Power Grid—0
Core Network Management Procedures for Self-Organized and Sustainable 5G Cellular Networks—0
Corticomorphic Hybrid CNN-SNN Architecture for EEG-based Low-footprint Low-latency Auditory Attention Detection—0
Cost-effective Machine Learning Inference Offload for Edge Computing—0
DeepEdge: A Deep Reinforcement Learning based Task Orchestrator for Edge Computing—0
Cooling-Aware Resource Allocation and Load Management for Mobile Edge Computing Systems—0
A Convergence Theory for Federated Average: Beyond Smoothness—0
Control-Oriented Power Allocation for Integrated Satellite-UAV Networks—0
cuVSLAM: CUDA accelerated visual odometry and mapping—0
D3PG: Dirichlet DDPG for Task Partitioning and Offloading With Constrained Hybrid Action Space in Mobile-Edge Computing—0
Damage Detection in Bridge Structures: An Edge Computing Approach—0
Controlling Chaos Using Edge Computing Hardware—0
DART: Depth-Enhanced Accurate and Real-Time Background Matting—0
Data-Driven Detection and Identification of IoT-Enabled Load-Altering Attacks in Power Grids—0
Data Quality in Edge Machine Learning: A State-of-the-Art Survey—0
Data Synopses Management based on a Deep Learning Model—0
A Review of Recent Advances of Binary Neural Networks for Edge Computing—0
Active Learning Solution on Distributed Edge Computing—0
A Quality-of-Service Compliance System using Federated Learning and Optimistic Rollups—0
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