Accueil Actualités Articles de recherche récents Tutoriels Ensembles de données Wiki SOTA Modèles LLM Classement GPU Événements

Français

Multi Label Image Classification On

Métriques

mAP (micro)

official split

Résultats

Résultats de performance de divers modèles sur ce benchmark

Nom du modèle	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

0 of 10 row(s) selected.