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Semantic Segmentation On Isprs Vaihingen

Métriques

Average F1

Overall Accuracy

Résultats

Résultats de performance de divers modèles sur ce benchmark

Nom du modèle	Average F1	Overall Accuracy	Paper Title	Repository
EfficientUNets and Transformers	93.7	91.8	Semantic Labeling of High Resolution Images Using EfficientUNets and Transformers	-
UNetFormer	90.4	91.0	UNetFormer: A UNet-like Transformer for Efficient Semantic Segmentation of Remote Sensing Urban Scene Imagery
ABCNet	-	90.7	ABCNet: Attentive Bilateral Contextual Network for Efficient Semantic Segmentation of Fine-Resolution Remote Sensing Images
LSKNet-T	91.7	93.6	LSKNet: A Foundation Lightweight Backbone for Remote Sensing
BANet	-	90.5	Transformer Meets Convolution: A Bilateral Awareness Network for Semantic Segmentation of Very Fine Resolution Urban Scene Images
SFA-Net	91.2	-	SFA-Net: Semantic Feature Adjustment Network for Remote Sensing Image Segmentation
LSKNet-S	91.8	93.6	LSKNet: A Foundation Lightweight Backbone for Remote Sensing
DC-Swin	90.7	91.6	A Novel Transformer Based Semantic Segmentation Scheme for Fine-Resolution Remote Sensing Images
FT-UNetFormer	91.3	91.6	UNetFormer: A UNet-like Transformer for Efficient Semantic Segmentation of Remote Sensing Urban Scene Imagery
UPerNet (SAP)	-	90.14	Stochastic Subsampling With Average Pooling	-
MANet	-	90.963	Multiattention network for semantic segmentation of fine-resolution remote sensing images	-

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