Lite-FENet: Lightweight multi-scale feature enrichment network for few-shot segmentation

Qun Li; Baoquan Sun; Bir Bhanu

doi:10.1016/j.knosys.2023.110887

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Lite-FENet: Lightweight multi-scale feature enrichment network for few-shot segmentation

Qun Li Baoquan Sun Bir Bhanu

Year: 2023 Journal: Knowledge-Based Systems Vol: 278 Pages: 110887-110887 Publisher: Elsevier BV

DOI: 10.1016/j.knosys.2023.110887

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Keywords:

Computer science Robustness (evolution) Pascal (unit) Segmentation Feature (linguistics) Focus (optics) Data mining Pattern recognition (psychology) Artificial intelligence Source code Shot (pellet)

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Advanced Neural Network Applications

Physical Sciences → Computer Science → Computer Vision and Pattern Recognition

Domain Adaptation and Few-Shot Learning

Physical Sciences → Computer Science → Artificial Intelligence

Advanced Image Processing Techniques

Physical Sciences → Computer Science → Computer Vision and Pattern Recognition

Lite-FENet: Lightweight multi-scale feature enrichment network for few-shot segmentation

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