ADE-CycleGAN: A Detail Enhanced Image Dehazing CycleGAN Network
Sensors, 2023 The preservation of image details in the defogging process is still one key challenge in the field of deep learning. The network uses the generation of confrontation loss and cyclic consistency loss to ensure that the generated defog image is similar to ...
Zhaozhao Yang, Huizhu Sun
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Applied Sciences (Switzerland), 2022 Since recognizing the location and extent of infarction is essential for diagnosis and treatment, many methods using deep learning have been reported. Generally, deep learning requires a large amount of training data.
Kuniaki Saito +2 more
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Deteriorated Characters Restoration for Early Japanese Books Using Enhanced CycleGAN
Heritage, 2023 Early Japanese books, classical humanities resources in Japan, have great historical and cultural value. However, Kuzushi-ji, the old character in early Japanese books, is scratched, faded ink, and lost due to weathering and deterioration over the years.
Lin Meng, Ryuto Ishibashi
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Multi-Head Mutual-Attention CycleGAN for Unpaired Image-to-Image Translation
IET Image Processing, 2020 The image‐to‐image translation, i.e. from source image domain to target image domain, has made significant progress in recent years. The most popular method for unpaired image‐to‐image translation is CycleGAN.
Yun Li
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DA-CycleGAN: Degradation-Adaptive Unpaired Super-Resolution for Historical Image Restoration [PDF]
Journal of ImagingHistorical images as the dominant method for documenting the world and its inhabitants can help us to better understand the real history. Due to the limited camera technology, historical images captured in the early to mid-20th century tend to be very ...
Lujun Zhai +3 more
doaj +2 more sources
Dose Prediction Deep Learning-Based Model for VMAT of Prostate Cancer Applying Magnetic Resonance Image (MRI) in Versa HD Linear Accelerator [PDF]
Advanced Biomedical ResearchBackground: Prostate cancer patients are commonly undergoing Radiotherapy (RT) and treatment planning system have a prominent role for dose calculation, while this would seem that dose distribution uncertainties of treatment planning system (TPS) may ...
Hossein Taheri +5 more
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Detail-Preserving CycleGAN-AdaIN Framework for Image-to-Ink Painting Translation
IEEE Access, 2020 Image translation tasks based on generative models have become an important research area, such as the general framework for unsupervised image translation-CycleGAN (Cycle-Consistent Generative Adversarial Networks).
Fengquan Zhang +2 more
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Development of head-to-head and longitudinal CycleGAN algorithm for MRI harmonization: validation in follow-up MRI evaluation in patients with brain metastasis [PDF]
Scientific ReportsVarious harmonization methods have been employed for obtaining MRI from different scanners. However, no study has yet focused on the clinical utility of the CycleGAN technique in reducing MRI interscanner variability for patients with brain metastasis ...
Hosung Hwang +8 more
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ESTOA: Revista de la Facultad de Arquitectura y Urbanismo de la Universidad de Cuenca, 2022 Historical maps contain significant data on the cultural, social, and urban character of cities. However, most historical maps utilize specific notation methods that differ from those commonly used today and converting these maps to more recent formats ...
Sema Alaçam +2 more
doaj +1 more source
Multi-Contrast MRI Image Synthesis Using Switchable Cycle-Consistent Generative Adversarial Networks
Diagnostics, 2022 Multi-contrast MRI images use different echo and repetition times to highlight different tissues. However, not all desired image contrasts may be available due to scan-time limitations, suboptimal signal-to-noise ratio, and/or image artifacts.
Huixian Zhang +4 more
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