RXDNFuse: A aggregated residual dense network for infrared and visible image fusion

Yongzhi Long; Haitao Jia; Yida Zhong; Yadong Jiang; Yuming Jia

doi:10.1016/j.inffus.2020.11.009

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JOURNAL ARTICLE

RXDNFuse: A aggregated residual dense network for infrared and visible image fusion

Yongzhi Long Haitao Jia Yida Zhong Yadong Jiang Yuming Jia

Year: 2020 Journal: Information Fusion Vol: 69 Pages: 128-141 Publisher: Elsevier BV

DOI: 10.1016/j.inffus.2020.11.009

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Keywords:

Computer science Fuse (electrical) Artificial intelligence Residual Fusion Pattern recognition (psychology) Representation (politics) Image fusion RGB color model Constraint (computer-aided design) Image (mathematics) Feature extraction Similarity (geometry) Computer vision Algorithm Mathematics

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Advanced Image Fusion Techniques

Physical Sciences → Engineering → Media Technology

Infrared Thermography in Medicine

Health Sciences → Medicine → Radiology, Nuclear Medicine and Imaging

Infrared Target Detection Methodologies

Physical Sciences → Engineering → Aerospace Engineering

RXDNFuse: A aggregated residual dense network for infrared and visible image fusion

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