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코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/MELALab/nela-gt
공식 코드NELA-GT-2022: A Large Multi-Labelled News Dataset for The Study of Misinformation in News Articles
https://github.com/MIC-DKFZ/nnDetection
공식 코드nnDetection: A Self-configuring Method for Medical Object Detection
https://github.com/MIDA-group/Cell-Detection
공식 코드A Comparison of Deep Learning Methods for Cell Detection in Digital Cytology
https://github.com/MIPT-Oulu/DeepWrist
공식 코드Critical Evaluation of Deep Neural Networks for Wrist Fracture Detection
https://github.com/MIT-HAN-LAB/temporal-shift-module
공식 코드TSM: Temporal Shift Module for Efficient Video Understanding
https://github.com/MIT-SPARK/TEASER-plusplus
공식 코드https://github.com/MMehdiMousavi/SuperCaustics
공식 코드https://github.com/Madave94/multi-annotator-toolkit
공식 코드https://github.com/MadryLab/cifar10_challenge
공식 코드Towards Deep Learning Models Resistant to Adversarial Attacks
https://github.com/MadryLab/mnist_challenge
공식 코드Towards Deep Learning Models Resistant to Adversarial Attacks
https://github.com/MahmudulHasan11085/Vision-Eagle-Attention
공식 코드Vision Eagle Attention: a new lens for advancing image classification
https://github.com/MahyarNajibi/SNIPER
공식 코드https://github.com/Maitreyapatel/speech-conversion-between-different-modalities
공식 코드CinC-GAN for Effective F0 prediction for Whisper-to-Normal Speech Conversion
https://github.com/MalongTech/research-fad
공식 코드Representation Sharing for Fast Object Detector Search and Beyond
https://github.com/Manjuphoenix/IndraEye
공식 코드IndraEye: Infrared Electro-Optical UAV-based Perception Dataset for Robust Downstream Tasks
https://github.com/MarcoMorik/Dynamic-Fairness
공식 코드https://github.com/MarioKrenn6240/SEMNET
공식 코드Predicting Research Trends with Semantic and Neural Networks with an application in Quantum Physics
https://github.com/MartinBuessemeyer/Artistic-Texture-Control
공식 코드Controlling Geometric Abstraction and Texture for Artistic Images
https://github.com/MartinHahner/LiDAR_fog_sim
공식 코드Fog Simulation on Real LiDAR Point Clouds for 3D Object Detection in Adverse Weather
https://github.com/MasterBin-IIAU/UNINEXT
공식 코드Universal Instance Perception as Object Discovery and Retrieval
https://github.com/MasterHow/CoBEV
공식 코드CoBEV: Elevating Roadside 3D Object Detection with Depth and Height Complementarity
https://github.com/MathLee/CMWNet
공식 코드Cross-Modal Weighting Network for RGB-D Salient Object Detection
https://github.com/MathLee/ICNet-for-RGBD-SOD
공식 코드https://github.com/MatteoFasulo/clef2025-checkthat
공식 코드https://github.com/MaurizioFD/RecSys2019_DeepLearning_Evaluation
공식 코드https://github.com/MaxReimann/WISE-Editing
공식 코드https://github.com/MaxReimann/video-stream-consistency
공식 코드Interactive Control over Temporal Consistency while Stylizing Video Streams
https://github.com/Mazin-Hnewa/MS-DAYOLO
공식 코드Multiscale Domain Adaptive YOLO for Cross-Domain Object Detection
https://github.com/MedChaabane/DEFT
공식 코드https://github.com/Media-Smart/vedadet/tree/main/configs/trainval/tinaface
공식 코드https://github.com/Megum1/DFST
공식 코드Deep Feature Space Trojan Attack of Neural Networks by Controlled Detoxification
https://github.com/Megvii-BaseDetection/AutoAssign
공식 코드AutoAssign: Differentiable Label Assignment for Dense Object Detection
https://github.com/Megvii-BaseDetection/BorderDet
공식 코드https://github.com/Megvii-BaseDetection/DeFCN
공식 코드End-to-End Object Detection with Fully Convolutional Network
https://github.com/Megvii-BaseDetection/DisAlign
공식 코드Distribution Alignment: A Unified Framework for Long-tail Visual Recognition
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.