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Full-Text Articles in Engineering
Transfer Learning, Model Interpretation, And Dataset Bias Analysis For Automated Violence Detection From Video, Erik Clemens
Transfer Learning, Model Interpretation, And Dataset Bias Analysis For Automated Violence Detection From Video, Erik Clemens
Master's Theses (2009 -)
Many communities have installed surveillance cameras in an effort to deter and respond to violence.Due to the difficulty of constantly monitoring such camera feeds, these systems are rarely used to provide real-time information. To enable rapid alerts and information for first responders, this thesis develops a proof-of-concept system capable of automatically detecting violence from video footage. This system is developed by fine-tuning a convolutional neural network that has previously demonstrated success on general action recognition tasks. This thesis explores two new techniques to improve the accuracy of the fine-tuned model. The first is a data augmentation technique that generates aspect …
Gaze Estimation And Tracking For Assisted Living Environments, Paris Her
Gaze Estimation And Tracking For Assisted Living Environments, Paris Her
Master's Theses (2009 -)
Assisted living environments must be able to efficiently and unobtrusively gather information on a person's well-being. Human gaze direction provides some of the strongest indicators of how a person behaves and interacts with their environment. To that end, this thesis proposes a gaze tracking method that uses a neural network regressor to estimate gaze direction from facial keypoints and integrates them over time using various temporal methods, specifically through moving averages and a Kalman filter. Our gaze regression model uses confidence gated units to handle cases of keypoint occlusion and is able to estimate its own prediction uncertainty. This approach …
Organ Segmentation Of Pediatric Computed Tomography (Ct) With Generative Adversarial Networks, Chi Nok Enoch Kan
Organ Segmentation Of Pediatric Computed Tomography (Ct) With Generative Adversarial Networks, Chi Nok Enoch Kan
Master's Theses (2009 -)
Accurately segmenting organs in abdominal computed tomography (CT) is crucial for many clinical applications such as organ-specific dose estimation. With the recent emergence of deep learning techniques for computer vision, many powerful frameworks are proposed for organ segmentation in abdominal CT images. A major problem with these state-of-the-art methods is that they depend on large amounts of training data to achieve high segmentation accuracy. Pediatric abdominal CTs are particularly hard to obtain since these children are much more sensitive to ionizing radiation than adults. It is extremely challenging to train automatic segmentation algorithms on pediatric CT volumes. To address these …
Deep Learning For Quantitative Susceptibility Mapping Reconstruction, Juan Liu
Deep Learning For Quantitative Susceptibility Mapping Reconstruction, Juan Liu
Dissertations (1934 -)
Quantitative susceptibility mapping (QSM) is a magnetic resonance imaging (MRI) technique that estimates tissue magnetic susceptibility from Larmor frequency offset measurements. The generation of QSM requires solving ill-posed background field removal (BFR) and field-to-source inversion problems. Incorrect BFR often introduces erroneous local field outputs and subsequently affects susceptibility quantification accuracy. Inaccurate field-to-source inversion often causes large susceptibility estimation errors that appear as streaking artifacts in the QSM, especially in massive hemorrhagic regions. Because current QSM techniques struggle to generate reliable QSM, the clinical translation of QSM is greatly hindered. Recently, deep learning (DL) has achieved state-of-the-art performance in many computer …
Apple Flower Detection Using Deep Convolutional Networks, Philipe A. Dias, Amy Tabb, Henry P. Medeiros
Apple Flower Detection Using Deep Convolutional Networks, Philipe A. Dias, Amy Tabb, Henry P. Medeiros
Electrical and Computer Engineering Faculty Research and Publications
To optimize fruit production, a portion of the flowers and fruitlets of apple trees must be removed early in the growing season. The proportion to be removed is determined by the bloom intensity, i.e., the number of flowers present in the orchard. Several automated computer vision systems have been proposed to estimate bloom intensity, but their overall performance is still far from satisfactory even in relatively controlled environments. With the goal of devising a technique for flower identification which is robust to clutter and to changes in illumination, this paper presents a method in which a pre-trained convolutional neural network …
Multi-View Face Recognition From Single Rgbd Models Of The Faces, Donghun Kim, Bharath Comandur, Henry P. Medeiros, Noha M. Elfiky, Avinash Kak
Multi-View Face Recognition From Single Rgbd Models Of The Faces, Donghun Kim, Bharath Comandur, Henry P. Medeiros, Noha M. Elfiky, Avinash Kak
Electrical and Computer Engineering Faculty Research and Publications
This work takes important steps towards solving the following problem of current interest: Assuming that each individual in a population can be modeled by a single frontal RGBD face image, is it possible to carry out face recognition for such a population using multiple 2D images captured from arbitrary viewpoints? Although the general problem as stated above is extremely challenging, it encompasses subproblems that can be addressed today. The subproblems addressed in this work relate to: (1) Generating a large set of viewpoint dependent face images from a single RGBD frontal image for each individual; (2) using hierarchical approaches based …