Distinguishing foreground and background alignment for unsupervised domain adaptative semantic segmentation

Jia Zhang; Wei Li; Zhixin Li

doi:10.1016/j.imavis.2022.104513

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Distinguishing foreground and background alignment for unsupervised domain adaptative semantic segmentation

Jia Zhang Wei Li Zhixin Li

Year: 2022 Journal: Image and Vision Computing Vol: 124 Pages: 104513-104513 Publisher: Elsevier BV

DOI: 10.1016/j.imavis.2022.104513

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Keywords:

Segmentation Computer science Artificial intelligence Pattern recognition (psychology) Feature (linguistics) Domain (mathematical analysis) Convolution (computer science) Channel (broadcasting) Image segmentation Computer vision Mathematics Artificial neural network

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Domain Adaptation and Few-Shot Learning

Physical Sciences → Computer Science → Artificial Intelligence

Multimodal Machine Learning Applications

Physical Sciences → Computer Science → Computer Vision and Pattern Recognition

COVID-19 diagnosis using AI

Health Sciences → Medicine → Radiology, Nuclear Medicine and Imaging

Distinguishing foreground and background alignment for unsupervised domain adaptative semantic segmentation

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