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코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://gitlab.com/vasishtduddu/FaultTolerantNN
공식 코드https://gitlab.idiap.ch/bob/bob.paper.ijcb2021_synthetic_dataset
공식 코드On the use of automatically generated synthetic image datasets for benchmarking face recognition
https://gitlab.lrz.de/hctl/Iris-Obfuscation-Benchmark
공식 코드Trade-offs in Privacy-Preserving Eye Tracking through Iris Obfuscation: A Benchmarking Study
https://huggingface.co/bdpc/src
공식 코드Beyond Document Page Classification: Design, Datasets, and Challenges
https://zenodo.org/record/8077639
공식 코드Multimodal Multi-User Surface Recognition with the Kernel Two-Sample Test
https://github.com/0jason000/wukong
Wukong: A 100 Million Large-scale Chinese Cross-modal Pre-training Benchmark
https://github.com/13274086/Tianchi2020
https://github.com/13952522076/mmdet0
https://github.com/13952522076/mmdet1
https://github.com/2023-MindSpore-1/ms-code-1
BenchENAS: A Benchmarking Platform for Evolutionary Neural Architecture Search
https://github.com/2023-MindSpore-1/ms-code-132
https://github.com/2023-MindSpore-1/ms-code-18/tree/main/lite-hrnet
https://github.com/2023-MindSpore-4/Code12/tree/main/MindFormers/clip
Learning Transferable Visual Models From Natural Language Supervision
https://github.com/2024-MindSpore-1/Code2/tree/main/model-1/clip
Learning Transferable Visual Models From Natural Language Supervision
https://github.com/329tyson/fai-ssl-challenge
Scaling and Benchmarking Self-Supervised Visual Representation Learning
https://github.com/ACEsuit/mace
Matbench Discovery -- A framework to evaluate machine learning crystal stability predictions
https://github.com/AFAgarap/cnn-svm
Fashion-MNIST: a Novel Image Dataset for Benchmarking Machine Learning Algorithms
https://github.com/AI4LIFE-GROUP/LLM_Explainer
OpenXAI: Towards a Transparent Evaluation of Model Explanations
https://github.com/Abdulk084/Intent_classification
An Evaluation Dataset for Intent Classification and Out-of-Scope Prediction
https://github.com/AcutronicRobotics/gym-gazebo2
gym-gazebo2, a toolkit for reinforcement learning using ROS 2 and Gazebo
https://github.com/AiLvv/mmdetection
https://github.com/AllenPeng0209/SaccadeNet
https://github.com/AmazingDD/daisyRec
DaisyRec 2.0: Benchmarking Recommendation for Rigorous Evaluation
https://github.com/AmenRa/rank_eval
MS MARCO: A Human Generated MAchine Reading COmprehension Dataset
https://github.com/AndresPMD/Clip_CMR
Learning Transferable Visual Models From Natural Language Supervision
https://github.com/AngusG/cleverhans-attacking-bnns
Technical Report on the CleverHans v2.1.0 Adversarial Examples Library
https://github.com/ArchieMeng/realsr-ncnn-vulkan-python
NTIRE 2020 Challenge on Real-World Image Super-Resolution: Methods and Results
https://github.com/Autonomous-Visual-Perception/detection-benchmark
https://github.com/AwesumMe/RetailClassification
https://github.com/AxelvL/AHPQ.jl
Accelerating Large-Scale Inference with Anisotropic Vector Quantization
https://github.com/BKAUTO/Trinocular-habitat-sim
https://github.com/Bam4d/GVGAI_GYM
https://github.com/BecauseOfGAN/capston
https://github.com/BecauseOfGAN/capstone
https://github.com/BigBinnie/Benchmarking-LLM-based-Machine-Translation-on-Cultural-Awareness
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.