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홈뉴스연구 논문튜토리얼데이터셋백과사전SOTALLM 모델GPU 랭킹컨퍼런스
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소개
한국어
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  1. 홈
  2. SOTA
  3. 다중 레이블 이미지 분류
  4. Multi Label Image Classification On

Multi Label Image Classification On

평가 지표

mAP (micro)
official split

평가 결과

이 벤치마크에서 각 모델의 성능 결과

모델 이름
mAP (micro)
official split
Paper TitleRepository
MoCo-v2 (ResNet18, fine tune)89.3NoSelf-supervised Learning in Remote Sensing: A Review
ResNet50--In-domain representation learning for remote sensing
DINO-MC88.75NoExtending global-local view alignment for self-supervised learning with remote sensing imagery
ResNet50-YesBenchmarking and scaling of deep learning models for land cover image classification
MoCo-v3 (ViT-S/16, fine tune)89.9NoSSL4EO-S12: A Large-Scale Multi-Modal, Multi-Temporal Dataset for Self-Supervised Learning in Earth Observation
MAE (ViT-S/16, fine tune)88.9NoSSL4EO-S12: A Large-Scale Multi-Modal, Multi-Temporal Dataset for Self-Supervised Learning in Earth Observation
ViTM/20-YesBenchmarking and scaling of deep learning models for land cover image classification
WideResNet-B5-ECA-YesBenchmarking and scaling of deep learning models for land cover image classification
MoCo-v2 (ResNet50, fine tune)91.8NoSSL4EO-S12: A Large-Scale Multi-Modal, Multi-Temporal Dataset for Self-Supervised Learning in Earth Observation
MLPMixer-YesBenchmarking and scaling of deep learning models for land cover image classification
0 of 10 row(s) selected.
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소개

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뉴스튜토리얼데이터셋백과사전

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