HyperAI

Video Polyp Segmentation On Sun Seg Hard

المقاييس

Dice
S-Measure
Sensitivity
mean E-measure
mean F-measure
weighted F-measure

النتائج

نتائج أداء النماذج المختلفة على هذا المعيار القياسي

جدول المقارنة
اسم النموذجDiceS-MeasureSensitivitymean E-measuremean F-measureweighted F-measure
النموذج 10.7080.7830.6180.7870.6840.636
progressively-normalized-self-attention0.6750.7670.5790.7550.6560.609
dynamic-context-sensitive-filtering-network0.3170.5140.3640.5220.3030.263
the-emergence-of-objectness-learning-zero0.2520.4720.2130.5270.1410.128
pranet-parallel-reverse-attention-network-for0.5980.7170.5120.7350.6070.544
unet-a-nested-u-net-architecture-for-medical--0.467---
sali-short-term-alignment-and-long-term-10.8220.8740.8300.9200.8220.790
matnet-motion-attentive-transition-network0.7120.7850.5790.7550.6450.578
see-more-know-more-unsupervised-video-object-10.6060.6700.3800.6270.5060.443
autosam-adapting-sam-to-medical-images-by0.7590.8220.7260.8660.7640.714
النموذج 110.7060.7860.6070.7750.6880.634
shallow-attention-network-for-polyp0.5980.7060.5050.7430.5800.526
video-polyp-segmentation-a-deep-learning0.7370.7970.6230.7930.7090.653
النموذج 140.5840.6820.4150.6600.5100.443
lgrnet-local-global-reciprocal-network-for0.865-----
self-prompting-polyp-segmentation-in0.9020.8940.8520.9410.932-
full-duplex-strategy-for-video-object0.6990.7240.4910.6940.6110.541
u-net-convolutional-networks-for-biomedical--0.429---