Results of comparison experiment.

<p>(Each group represents an evaluation metric, with different colors signifying different algorithms. The height of the bars indicates the magnitude of the metric, and the line segments on top of the bars represent the standard deviation of the metric. The taller the bar, the better the perfo...

وصف كامل

محفوظ في:

التفاصيل البيبلوغرافية
المؤلف الرئيسي:	Jia Li (160557) (author)
مؤلفون آخرون:	Yu-Qian Zhou (7449311) (author)
منشور في:	2025
الموضوعات:	Biochemistry Biotechnology Space Science Biological Sciences not elsewhere classified Information Systems not elsewhere classified wider clinical use reducing annotation costs outperforming existing methods introduced new methods common yet often branch loss function achieve comparable results 912 &# 8212 using active learning combine active learning tackle related challenges identifying additional features leverages data correlation inefficient data labeling novel classification algorithm enhance feature extraction gallbladder ultrasound dataset supervised learning integration supervised learning feature extraction deep learning still challenges full dataset clustering features ultrasound imaging ultrasound images labeled data typically characterized poor prognosis paper introduces order information mshop module model stability late detection fine textures findings demonstrate effectively captures early identification diagnosed malignancy
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Results of comparison experiment.

مواد مشابهة