Results 11 to 20 of about 1,040 (193)
Artificial Intelligence (Enhanced Super-Resolution Generative Adversarial Network) for Calcium Deblooming in Coronary Computed Tomography Angiography: A Feasibility Study [PDF]
Diagnostics, 2022 Background: The presence of heavy calcification in the coronary artery always presents a challenge for coronary computed tomography angiography (CCTA) in assessing the degree of coronary stenosis due to blooming artifacts associated with calcified ...
Zhonghua Sun, Curtise K. C. Ng
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MRI Super Resolution Using ESRGAN
, 2023 Abstract— Magnetic resonance imaging (MRI) at high spatial resolution is essential for accurate detailed and quantitative physiologic assessment. However, single image super resolution (SISR) techniques with traditional long scan times, reduced spatial masking, and low signal-to-noise ratio (SNR) to acquire MR images with high spatial resolution have ...
Savio Jose, Bijimol T K
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Enhancement of Diabetic Retinopathy Prognostication Using Deep Learning, CLAHE, and ESRGAN
Diagnostics, 2023 One of the primary causes of blindness in the diabetic population is diabetic retinopathy (DR). Many people could have their sight saved if only DR were detected and treated in time.
Ghadah Alwakid +2 more
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Uncertainty Estimation for Super-Resolution Using ESRGAN
Proceedings of the 20th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and ApplicationsDeep Learning-based image super-resolution (SR) has been gaining traction with the aid of Generative Adversarial Networks. Models like SRGAN and ESRGAN are constantly ranked between the best image SR tools. However, they lack principled ways for estimating predictive uncertainty.
Maniraj Sai Adapa +2 more
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Remote Sensing, 2020 The detection performance of small objects in remote sensing images has not been satisfactory compared to large objects, especially in low-resolution and noisy images.
Jakaria Rabbi +4 more
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Heliyon, 2023 The proposal of perceptual loss solves the over-smoothing problem of images caused by pixel-wise loss and improves the visual quality of the images, but it also inevitably produces a large number of artifacts and distortions in images.
Jie Song +5 more
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Crop Disease Classification on Inadequate Low-Resolution Target Images
Sensors, 2020 Currently, various agricultural image classification tasks are carried out on high-resolution images. However, in some cases, we cannot get enough high-resolution images for classification, which significantly affects classification performance.
Juan Wen +3 more
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Super-Resolution Reconstruction of Cell Images Based on Generative Adversarial Networks
IEEE AccessIn this study, we introduce Light-ESRGAN, a novel cellular image super-resolution reconstruction model utilizing Generative Adversarial Networks (GANs).
Bin Pan, Yifeng Du, Xiaoming Guo
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Peningkatan Performa Pengenalan Wajah pada Gambar Low-Resolution Menggunakan Metode Super-Resolution [PDF]
Jurnal Teknologi Informasi dan Ilmu KomputerKartu Tanda Penduduk Elektronik (KTP-el) merupakan identitas wajib bagi penduduk Indonesia. Penyimpanan pada cip KTP-el yang mana selain digunakan untuk menyimpan gambar potret wajah individu, juga harus dapat menyimpan identitas lain seperti biodata ...
Muhammad Imaduddin Abdur Rohim +6 more
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CoRRWith the robust development of technology, license plate recognition technology can now be properly applied in various scenarios, such as road monitoring, tracking of stolen vehicles, detection at parking lot entrances and exits, and so on. However, the precondition for these applications to function normally is that the license plate must be 'clear ...
Wang, Ching-Hsiang
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