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Edge-computing

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코드

관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/salimkhazem/polygonet

공식 코드

PolygoNet: Leveraging Simplified Polygonal Representation for Effective Image Classification

https://github.com/scopex-asu/doctor

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DOCTOR: Dynamic On-Chip Temporal Variation Remediation Toward Self-Corrected Photonic Tensor Accelerators

https://github.com/sefaburakokcu/finn-quantized-yolo

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LPYOLO: Low Precision YOLO for Face Detection on FPGA

https://github.com/shaojiawei07/BottleNetPlusPlus

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BottleNet++: An End-to-End Approach for Feature Compression in Device-Edge Co-Inference Systems

https://github.com/shaojiawei07/Edge_Inference_three-step_framework

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Communication-Computation Trade-Off in Resource-Constrained Edge Inference

https://github.com/sharc-lab/residual-inr

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Residual-INR: Communication Efficient On-Device Learning Using Implicit Neural Representation

https://github.com/simdis/Adaptive-TML

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Tiny Machine Learning for Concept Drift

https://github.com/simeonallmendinger/collafuse_imagen

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CollaFuse: Navigating Limited Resources and Privacy in Collaborative Generative AI

https://github.com/sunnyxuejj/FedLPS-main

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Learnable Sparse Customization in Heterogeneous Edge Computing

https://github.com/tesfayz/ccm_madrl_mec

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Combinatorial Client-Master Multiagent Deep Reinforcement Learning for Task Offloading in Mobile Edge Computing

https://github.com/teto1992/declace

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Continuous reasoning for adaptive container image distribution in the cloud-edge continuum

https://github.com/trung-pham-dinh/CNN-on-FPGA

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An FPGA-based Solution for Convolution Operation Acceleration

https://github.com/tusharsangam/transvisdrone

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TransVisDrone: Spatio-Temporal Transformer for Vision-based Drone-to-Drone Detection in Aerial Videos

https://github.com/uic-jq/iopo

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A Fast Task Offloading Optimization Framework for IRS-Assisted Multi-Access Edge Computing System

https://github.com/uidmice/placement-rl

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GiPH: Generalizable Placement Learning for Adaptive Heterogeneous Computing

https://github.com/uva-dsa/ems-pipeline

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Real-Time Multimodal Cognitive Assistant for Emergency Medical Services

https://github.com/victorcroisfelt/mec-with-ris-control

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Control Aspects for Using RIS in Latency-Constrained Mobile Edge Computing

https://github.com/waittim/mask-detector

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WearMask: Fast In-browser Face Mask Detection with Serverless Edge Computing for COVID-19

https://github.com/wangxb96/awesome-ai-on-the-edge

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Optimizing Edge AI: A Comprehensive Survey on Data, Model, and System Strategies

https://github.com/whu-usi3dv/mobile-seed

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Mobile-Seed: Joint Semantic Segmentation and Boundary Detection for Mobile Robots

https://github.com/wisegamgee/hyperad

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ERX: A Fast Real-Time Anomaly Detection Algorithm for Hyperspectral Line Scanning

https://github.com/wiselabcmu/pitot

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Interference-Aware Edge Runtime Prediction with Conformal Matrix Completion

https://github.com/word-ky/Edge-TOOLBOX

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Efficient Detection Framework Adaptation for Edge Computing: A Plug-and-play Neural Network Toolbox Enabling Edge Deployment

https://github.com/xingqiuhe/dpds

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Age-Based Scheduling for Mobile Edge Computing: A Deep Reinforcement Learning Approach

https://github.com/yangjc97/memristor-sde-diffusion

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Resistive Memory-based Neural Differential Equation Solver for Score-based Diffusion Model

https://github.com/yangshunzhi1994/EdgeCNN

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EdgeCNN: Convolutional Neural Network Classification Model with small inputs for Edge Computing

https://github.com/yoshitomo-matsubara/hnd-ghnd-object-detectors

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Split Computing for Complex Object Detectors: Challenges and Preliminary Results

https://github.com/yoshitomo-matsubara/ladon-multi-task-sc2

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A Multi-task Supervised Compression Model for Split Computing

https://github.com/yoshitomo-matsubara/sc2-benchmark

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SC2 Benchmark: Supervised Compression for Split Computing

https://github.com/yoshitomo-matsubara/supervised-compression

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Supervised Compression for Resource-Constrained Edge Computing Systems

https://github.com/yu-utah/respect

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RESPECT: Reinforcement Learning based Edge Scheduling on Pipelined Coral Edge TPUs

https://github.com/yunchengwang/greenkgc

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GreenKGC: A Lightweight Knowledge Graph Completion Method

https://github.com/zalandoresearch/fashion-mnist

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Spectral Pruning for Recurrent Neural Networks

https://github.com/zeyuzhangzyz/axiomvision

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AxiomVision: Accuracy-Guaranteed Adaptive Visual Model Selection for Perspective-Aware Video Analytics

https://github.com/zhaolanhuang/u-toe

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U-TOE: Universal TinyML On-board Evaluation Toolkit for Low-Power IoT

https://github.com/ziongo6/hawkdrive

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HawkDrive: A Transformer-driven Visual Perception System for Autonomous Driving in Night Scene

출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.