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License Plate Image Quality Enhancement Utilizing Super Resolution Generative Adversarial Networks, Mark Moelter
License Plate Image Quality Enhancement Utilizing Super Resolution Generative Adversarial Networks, Mark Moelter
Electronic Theses and Dissertations
This thesis focuses primarily on enhancing the image quality of blurred license plates through the use of Super-Resolution Generative Adversarial Networks (SRGANs) [1]. We propose a synthetic dataset with SRGAN model to promote blurred image quality enhancement, and allow for model evaluation on a multitude of image input and output size combinations. SRGAN is mainly used for low-resolution image enhancement, but by heavily blurring the input images, the model is tested on its ability to blindly deblur and upsample images to the desired super-resolution (SR) size. The model enhances the image quality to nearly that of the reference images. The …
Cascaded Deep Learning Network For Postearthquake Bridge Serviceability Assessment, Youjeong Jang
Cascaded Deep Learning Network For Postearthquake Bridge Serviceability Assessment, Youjeong Jang
Electronic Theses and Dissertations
Damages assessment of bridges is important to derive immediate response after severe events to decide serviceability. Especially, past earthquakes have proven the vulnerability of bridges with insufficient detailing. Due to lack of a national and unified post-earthquake inspection procedure for bridges, conventional damage assessments are performed by sending professional personnel to the onsite, detecting visually and measuring the damage state. To get accurate and fast damage result of bridge condition is important to save not only lives but also costs.
There have been studies using image processing techniques to assess damage of bridge column without sending individual to onsite. Convolutional …