Synthetic IR Image Refinement Using Adversarial Learning With Bidirectional Mappings

Synthetic IR Image Refinement Using Adversarial Learning With Bidirectional Mappings

Collecting a large dataset of real infrared (IR) images is expensive, time-consuming, and even unavailable in some specific scenarios. With recent progress in machine learning, it has become more feasible to replace real IR images with qualified synthetic IR images in learning-based IR systems. Howe...

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Bibliographic Details
Main Authors: Ruiheng Zhang, Chengpo Mu, Min Xu, Lixin Xu, Qiaolin Shi, Junbo Wang
Format: Article
Language:English
Published: IEEE 2019-01-01
Series:IEEE Access
Subjects:
Infrared simulation
synthetic refinement
convolutional neural networks
adversarial learning
Online Access:https://ieeexplore.ieee.org/document/8871125/

Internet

https://ieeexplore.ieee.org/document/8871125/

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