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Full-Text Articles in Engineering
A Computer Vision-Based Method For Bolt Loosening Detection, Savannah Burdette
A Computer Vision-Based Method For Bolt Loosening Detection, Savannah Burdette
Honors Theses
Routine bolt-loosening inspection plays an essential role in managing and preventing the degradation of our nation’s highway bridges over time. Neglecting to perform these inspections could result in public safety concerns. The study of this thesis develops a cost-effective method of bolt-loosening detection based on computer vision. To this end, two input images of the bolted connections are collected at two different inspection times. The feature points are then identified from the input images, based on which a geometric transformation matrix is applied to correct any perspective differences between the two images. Next, we select the image patches of the …
Conditional Variational Autoencoder (Cvae) For The Augmentation Of Ecl Biosensor Data, Matthew Dulcich
Conditional Variational Autoencoder (Cvae) For The Augmentation Of Ecl Biosensor Data, Matthew Dulcich
Honors Theses
Machine Learning (ML) is vastly improving the world, from computer vision to fully self-driving cars, we are now able accomplish objectives that were thought to only be dreams. In order to train ML models accurately, they require mountains of information to work with, but sometimes it becomes impossible to collect the data needed, so we turn to data augmentation. In this project we use a conditional variational auto encoder to supplement the original video electrochemiluminescence biosensor dataset, in order to increase the accuracy of a future classification model. In other words, using a cVAE we will create unique realistic videos …
Perceptually Improved Medical Image Translations Using Conditional Generative Adversarial Networks, Anurag Vaidya
Perceptually Improved Medical Image Translations Using Conditional Generative Adversarial Networks, Anurag Vaidya
Honors Theses
Magnetic resonance imaging (MRI) can help visualize various brain regions. Typical MRI sequences consist of T1-weighted sequence (favorable for observing large brain structures), T2-weighted sequence (useful for pathology), and T2-FLAIR scan (useful for pathology with suppression of signal from water). While these different scans provide complementary information, acquiring them leads to acquisition times of ~1 hour and an average cost of $2,600, presenting significant barriers. To reduce these costs associated with brain MRIs, we present pTransGAN, a generative adversarial network capable of translating both healthy and unhealthy T1 scans into T2 scans. We show that the addition of non-adversarial …