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Multi Label Image Classification On

評価指標

mAP (micro)
official split

評価結果

このベンチマークにおける各モデルのパフォーマンス結果

モデル名
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-
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Multi Label Image Classification On | SOTA | HyperAI超神経