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Multi Label Image Classification On

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mAP (micro)

official split

Ergebnisse

Leistungsergebnisse verschiedener Modelle zu diesem Benchmark

Modellname	mAP (micro)	official split	Paper Title	Repository
MoCo-v2 (ResNet18, fine tune)	89.3	No	Self-supervised Learning in Remote Sensing: A Review	-
ResNet50	-	-	In-domain representation learning for remote sensing	-
DINO-MC	88.75	No	Extending global-local view alignment for self-supervised learning with remote sensing imagery	-
ResNet50	-	Yes	Benchmarking and scaling of deep learning models for land cover image classification	-
MoCo-v3 (ViT-S/16, fine tune)	89.9	No	SSL4EO-S12: A Large-Scale Multi-Modal, Multi-Temporal Dataset for Self-Supervised Learning in Earth Observation	-
MAE (ViT-S/16, fine tune)	88.9	No	SSL4EO-S12: A Large-Scale Multi-Modal, Multi-Temporal Dataset for Self-Supervised Learning in Earth Observation	-
ViTM/20	-	Yes	Benchmarking and scaling of deep learning models for land cover image classification	-
WideResNet-B5-ECA	-	Yes	Benchmarking and scaling of deep learning models for land cover image classification	-
MoCo-v2 (ResNet50, fine tune)	91.8	No	SSL4EO-S12: A Large-Scale Multi-Modal, Multi-Temporal Dataset for Self-Supervised Learning in Earth Observation	-
MLPMixer	-	Yes	Benchmarking and scaling of deep learning models for land cover image classification	-

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Multi Label Image Classification On | SOTA | HyperAI