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Edge-computing
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Deep Learning on EDGE devices
논문
이 태스크와 하위 분야의 관련 논문입니다. 실제 성능 비교는 평가 결과에서 확인하세요.
QTCAJOSA: Low-Complexity Joint Offloading and Subchannel Allocation for NTN-Enabled IoMT
Efficient Training of Large-Scale AI Models Through Federated Mixture-of-Experts: A System-Level Approach
Hierarchical Task Offloading for UAV-Assisted Vehicular Edge Computing via Deep Reinforcement Learning
ECORE: Energy-Conscious Optimized Routing for Deep Learning Models at the Edge
QS4D: Quantization-aware training for efficient hardware deployment of structured state-space sequential models
MAIZX: A Carbon-Aware Framework for Optimizing Cloud Computing Emissions
Federated Learning-Based Data Collaboration Method for Enhancing Edge Cloud AI System Security Using Large Language Models
Joint Computation Offloading and Resource Allocation for Uncertain Maritime MEC via Cooperation of UAVs and Vessels
One-Shot Neural Architecture Search with Network Similarity Directed Initialization for Pathological Image Classification
Dual‑detector Re‑optimization for Federated Weakly Supervised Video Anomaly Detection Via Adaptive Dynamic Recursive Mapping
Multi-dimensional Autoscaling of Processing Services: A Comparison of Agent-based Methods
SLED: A Speculative LLM Decoding Framework for Efficient Edge Serving
HASFL: Heterogeneity-aware Split Federated Learning over Edge Computing Systems
Agile Reinforcement Learning for Real-Time Task Scheduling in Edge Computing
Optimal Task Offloading with Firm Deadlines for Mobile Edge Computing Systems
Computation Capacity Maximization for Pinching Antennas-Assisted Wireless Powered MEC Systems
Federated Learning on Stochastic Neural Networks
Design and Implementation of a RISC-V SoC with Custom DSP Accelerators for Edge Computing
Edge-Enabled Collaborative Object Detection for Real-Time Multi-Vehicle Perception
Cloud-Based Interoperability in Residential Energy Systems
An SCMA Receiver for 6G NTN based on Multi-Task Learning
cuVSLAM: CUDA accelerated visual odometry and mapping
Sylva: Tailoring Personalized Adversarial Defense in Pre-trained Models via Collaborative Fine-tuning
A Novel Deep Reinforcement Learning Method for Computation Offloading in Multi-User Mobile Edge Computing with Decentralization
Generative AI for Predicting 2D and 3D Wildfire Spread: Beyond Physics-Based Models and Traditional Deep Learning
Maximizing the Promptness of Metaverse Systems using Edge Computing by Deep Reinforcement Learning
FAuNO: Semi-Asynchronous Federated Reinforcement Learning Framework for Task Offloading in Edge Systems
AI-Driven Vehicle Condition Monitoring with Cell-Aware Edge Service Migration
Computation- and Communication-Efficient Online FL for Resource-Constrained Aerial Vehicles
Edge Computing for Physics-Driven AI in Computational MRI: A Feasibility Study
Knowledge Distillation for Reservoir-based Classifier: Human Activity Recognition
Stochastic Geometry-Based Performance Evaluation for LEO Satellite-Assisted Space Caching
FedSKC: Federated Learning with Non-IID Data via Structural Knowledge Collaboration
Clip4Retrofit: Enabling Real-Time Image Labeling on Edge Devices via Cross-Architecture CLIP Distillation
A Two-Stage Data Selection Framework for Data-Efficient Model Training on Edge Devices
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.