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Edge-computing

Deep Learning on EDGE devices

Papers

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Showing 476–500 of 1279 papers

TitleStatusHype
Orchestration of Emulator Assisted Mobile Edge Tuning for AI Foundation Models: A Multi-Agent Deep Reinforcement Learning Approach—0
FedPEAT: Convergence of Federated Learning, Parameter-Efficient Fine Tuning, and Emulator Assisted Tuning for Artificial Intelligence Foundation Models with Mobile Edge Computing—0
LC-TTFS: Towards Lossless Network Conversion for Spiking Neural Networks with TTFS Coding—0
Poster: Real-Time Object Substitution for Mobile Diminished Reality with Edge Computing—0
An Efficient Imbalance-Aware Federated Learning Approach for Wearable Healthcare with Autoregressive Ratio Observation—0
Mobile Traffic Prediction at the Edge Through Distributed and Deep Transfer Learning—0
Unveiling Energy Efficiency in Deep Learning: Measurement, Prediction, and Scoring across Edge Devices—0
Cloud-Magnetic Resonance Imaging System: In the Era of 6G and Artificial Intelligence—0
A Blockchain-empowered Multi-Aggregator Federated Learning Architecture in Edge Computing with Deep Reinforcement Learning Optimization—0
Performance/power assessment of CNN packages on embedded automotive platforms—0
Edge Computing-Enabled Road Condition Monitoring: System Development and Evaluation—0
A Lightweight Video Anomaly Detection Model with Weak Supervision and Adaptive Instance Selection—0
EdgeFD: An Edge-Friendly Drift-Aware Fault Diagnosis System for Industrial IoT—0
Federated Fine-Tuning of LLMs on the Very Edge: The Good, the Bad, the Ugly—0
Quantum-Based Feature Selection for Multi-classification Problem in Complex Systems with Edge Computing—0
DYNAP-SE2: a scalable multi-core dynamic neuromorphic asynchronous spiking neural network processor—0
Quantization of Deep Neural Networks to facilitate self-correction of weights on Phase Change Memory-based analog hardware—0
Energy-Efficient Secure Offloading System Designed via UAV-Mounted Intelligent Reflecting Surface for Resilience Enhancement—0
Adversarial Machine Learning in Latent Representations of Neural NetworksCode0
Pushing Large Language Models to the 6G Edge: Vision, Challenges, and Opportunities—0
Online Resource Allocation for Semantic-Aware Edge Computing Systems—0
Resource Allocation for Semantic-Aware Mobile Edge Computing Systems—0
Containing Analog Data Deluge at Edge through Frequency-Domain Compression in Collaborative Compute-in-Memory Networks—0
Task Graph offloading via Deep Reinforcement Learning in Mobile Edge Computing—0
Exploration of TPUs for AI Applications—0
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