Results 11 to 20 of about 2,512,732 (195)
Impact of Image Resolution on Deep Learning Performance in Endoscopy Image Classification: An Experimental Study Using a Large Dataset of Endoscopic Images [PDF]
Diagnostics, 2021 Recent trials have evaluated the efficacy of deep convolutional neural network (CNN)-based AI systems to improve lesion detection and characterization in endoscopy.
Vajira Thambawita +5 more
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Mastcam Image Resolution Enhancement with Application to Disparity Map Generation for Stereo Images with Different Resolutions [PDF]
Sensors, 2019 In this paper, we introduce an in-depth application of high-resolution disparity map estimation using stereo images from Mars Curiosity rover’s Mastcams, which have two imagers with different resolutions.
Bulent Ayhan, Chiman Kwan
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Super-resolution Ultrasound Imaging [PDF]
Ultrasound in Medicine & Biology, 2020 Ultrasound in medicine & biology 46(4), 865-891 (2020).
Christensen-Jeffries, Kirsten +11 more
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HIGH RESOLUTION IMAGE CLASSIFICATION [PDF]
المجلة العراقية للعلوم الاحصائية, 2005 Classification is an important field with many applications. In particular, the classification of digital imagery has important applications in the mapping community.
Wasfi Taher Saalih
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IET Image Processing, 2023 With constant advances in deep learning methods as applied to image processing, deep convolutional neural networks (CNNs) have been widely explored in single‐image super‐resolution (SISR) problems and have attained significant success.
Yuanyuan Liu +3 more
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Enhanced Dense Space Attention Network for Super-Resolution Construction From Single Input Image
IEEE Access, 2021 In some applications, such as surveillance and biometrics, image enlargement is required to inspect small details on the image. One of the image enlargement approaches is by using convolutional neural network (CNN)-based super-resolution construction ...
Yoong Khang Ooi +2 more
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Reliable Perceptual Loss Computation for GAN-Based Super-Resolution With Edge Texture Metric
IEEE Access, 2021 Super-resolution (SR) is an ill-posed problem. Generating high-resolution (HR) images from low-resolution (LR) images remains a major challenge. Recently, SR methods based on deep convolutional neural networks (DCN) have been developed with impressive ...
J. Kim, C. Lee
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Super resolution for root imaging [PDF]
Applications in Plant Sciences, 2020 PremiseHigh‐resolution cameras are very helpful for plant phenotyping as their images enable tasks such as target vs. background discrimination and the measurement and analysis of fine above‐ground plant attributes. However, the acquisition of high‐resolution images of plant roots is more challenging than above‐ground data collection.
Jose F. Ruiz‐Munoz +4 more
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Point cloud super‐resolution based on geometric constraints
IET Computer Vision, 2021 Among all digital representations we have for real physical objects, three‐dimensional (3D) is arguably the most expressive encoding. But due to the limitations of 3D scanning equipment, point cloud often becomes sparse or partially missing.
Xiaoqiang Li, Jitao Liu, Songmin Dai
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Image resolution enhancement using dual-tree complex wavelet transform [PDF]
, 2010 In this letter, a complex wavelet-domain image resolution enhancement algorithm based on the estimation of wavelet coefficients is proposed. The method uses a forward and inverse dual-tree complex wavelet transform (DT-CWT) to construct a high-resolution
Tjahjadi, Tardi, Çelik, Turgay
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