Browsing by Subject "deep learning"
Now showing items 1-13 of 13
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Automated Location of Bird Roosts Using NEXRAD Data and Image Segmentation
(2020)Weather surveillance radars can effectively detect flying animals, such as groups of birds, bats, and insects. Further, these radars are demonstrably useful for detecting the existence of certain bird roosting locations, ... -
Deep Autoencoders for Cross-Modal Retrieval
(2019-05-01)Increased accuracy and affordability of depth sensors such as Kinect has created a great depth-data source for 3D processing. Specifically, 3D model retrieval is attracting attention in the field of computer vision and ... -
Development of in-field data acquisition systems and machine learning-based data processing and analysis approaches for turfgrass quality rating and peanut flower detection
(2022-07)Digital image processing and machine vision techniques provide scientists with an objective measure of crop quality that adds to the validity of study results without burdening the evaluation process. This dissertation ... -
Holistic indoor scene understanding by context supported instance segmentation
(2020-12)Intelligent robots require advanced vision capabilities to perceive and interact with the real physical world. While computer vision has made great strides in recent years, its predominant paradigm still focuses on building ... -
Interpreting natural language processing (NLP) models and lifting their limitations
(2021-07)There have been many advances in the artificial intelligence field due to the emergence of deep learning and big data. In almost all sub-fields, artificial neural networks have reached or exceeded human-level performance. ... -
Physics-guided machine learning for turbulence closure and reduced-order modeling
(2022-07)A recent advance in scientific machine learning has started to show promising results in fluid mechanics. Despite their early success, the application of data-driven methods to turbulent flow simulation is non-trivial due ... -
Sematic understanding of large-scale outdoor web images: From emotion recognition to scene classification
(2020-12)Facial expression recognition and scene-based image clustering are very popular topics in the fields of human-computer interaction and computer vision. Their relationship has been rarely investigated but is a very attractive ... -
Too many cooks in the kitchen? A comprehensive comparison of NGO spending and development in Nepal
(2022-05)There are over 51,000 non-governmental organizations (NGOs) registered in Nepal, yet the country continually ranks low in various measures of human development. As is the case in many developing countries, NGOs operate ... -
Using Deep Learning to Improve Prediction and Understanding of High-impact Weather
(2020-05)This dissertation describes the application of convolutional neural networks (CNN), a type of deep-learning method, to high-impact weather. CNNs are specially designed to learn directly from spatial grids, which improves ... -
Using machine learning methods to improve healthcare delivery in diabetes management
(2022-07)This dissertation includes three studies, all focusing on Analytics and Patients information for improving diabetes management, namely educating patients and early detection of comorbidities. In these studies, we develop ... -
Visibility Estimation from Camera Images Using Deep Learning
(2023-08-04)Atmospheric visibility is an important and complex meteorological variable that directly affects safe and reliable transportation. Specifically, declining visibility can pose an increased risk to automotive, aviation, and ... -
Visualization and intelligent solutions for big pavement data
(2018-07)Pavement visualization and crack detection are two important components supporting modern pavement condition survey. In this dissertation, two major goals are accomplished based on implementable algorithms. 1) The long-distance ... -
Website Fingerprinting Attacks
(2019-05-01)Most privacy-conscious users utilize HTTPS and an anonymity network such as Tor to mask source and destination IP addresses. It has been shown that encrypted and anonymized network traffic traces can still leak information ...