Detection of Concrete Cracks Using Machine Learning and RAW Ultra-High-Definition Images
This document discusses the detection of concrete cracks using machine learning and ultra-high-definition images from RAW data. By processing RAW data output from commercially available digital cameras through techniques such as restoration and synthesis using machine learning, we can enhance the detection accuracy of concrete cracks by producing high-definition images that are undistorted, similar to human vision. [Contents (excerpt)] ■ Introduction ■ Image Processing Using Machine Learning ■ Super Resolution Stepless Zoom ■ Keep Resolution Mapping ■ Optical Learning *For more details, please refer to the PDF document or feel free to contact us.
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【Other Published Content】 ■Demosaic Phase Shift Development ■Crack Detection System ■RAW Development and Aberration Restoration ■Image Composition and File Splitting ■Image Composition and File Splitting Viewer ■Crack Detection ■Difference Detection *For more details, please refer to the PDF document or feel free to contact us.
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Realop Co., Ltd. provides image processing-related intellectual property rights licensing (such as our Optical Learning® technology), software development and sales, and technical consulting services to offer differentiated image processing technologies to our partner companies, supporting their revenue growth by enhancing their product capabilities. With years of experience, we develop learning-based super-resolution algorithms that take into account the characteristics of hardware and GPUs, so please feel free to contact us if you have any requests.