AFCANet: An adaptive feature concatenate attention network for multi-focus image fusion-Reference-Cited by-同舟云学术

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AFCANet: An adaptive feature concatenate attention network for multi-focus image fusion

Published:2023-10 Issue:9 Volume:35 Page:101751
ISSN:1319-1578
Container-title:Journal of King Saud University - Computer and Information Sciences
language:en
Short-container-title:Journal of King Saud University - Computer and Information Sciences

Author:

Liu Shuaiqi,Peng Weijian,Liu Yali,Zhao Jie,Su Yonggang,Zhang Yudong^ORCID

Publisher

Elsevier BV

Subject

General Computer Science

Reference41 articles.

1. Multi-scale guided image and video fusion: A fast and efficient approach[J];Bavirisetti;Circuits Systems Signal Process.,2019

2. Multi-focus Image Fusion using Neutrosophic based Wavelet Transform[J];Bhat;Appl. Soft Comput.,2021

3. A new automated quality assessment algorithm for image fusion[J];Chen;Image Vis. Comput.,2009

4. Haghighat, M., Razian, M.A. 2014. Fast-FMI: non-reference image fusion metric[C]// IEEE 8th International Conference on Application of Information and Communication Technologies (AICT). IEEE, 1-3.

5. Guided image filtering[J];He;IEEE Trans. Pattern Anal. Mach. Intell.,2012

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1. EDOM-MFIF: an end-to-end decision optimization model for multi-focus image fusion;Applied Intelligence;2024-08-20

2. Cross-scale Vision Transformer for crowd localization;Journal of King Saud University - Computer and Information Sciences;2024-02

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