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Social and Behavioral Sciences Commons™
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Full-Text Articles in Social and Behavioral Sciences
Identifying Smokestacks In Remotely Sensed Imagery Via Deep Learning Algorithms, Kenneth Moss
Identifying Smokestacks In Remotely Sensed Imagery Via Deep Learning Algorithms, Kenneth Moss
Masters Theses
Locating smokestacks in remote sensing imagery is a crucial first step to calculating smokestack heights, which allows for the accurate modeling of dioxin pollution spread and the study of resulting health impacts. In the interest of automating this process, this thesis examines deep learning networks and how changes in input datasets and network architecture affect image detection accuracy. This initial image detection serves as the first step in automated object recognition and height calculation. While this is applicable to general land use classification, this study specifically addresses detecting smokestack images. Different dataset scenarios are generated from the massive Functional Map …
Deep Learning For Remote Sensing Image Processing, Yan Lu
Deep Learning For Remote Sensing Image Processing, Yan Lu
Computational Modeling & Simulation Engineering Theses & Dissertations
Remote sensing images have many applications such as ground object detection, environmental change monitoring, urban growth monitoring and natural disaster damage assessment. As of 2019, there were roughly 700 satellites listing “earth observation” as their primary application. Both spatial and temporal resolutions of satellite images have improved consistently in recent years and provided opportunities in resolving fine details on the Earth's surface. In the past decade, deep learning techniques have revolutionized many applications in the field of computer vision but have not fully been explored in remote sensing image processing. In this dissertation, several state-of-the-art deep learning models have been …
Deep Learning For Overhead Imagery: Algorithms And Applications, Anthony Manuel Ortiz Cepeda
Deep Learning For Overhead Imagery: Algorithms And Applications, Anthony Manuel Ortiz Cepeda
Open Access Theses & Dissertations
Remote sensing using overhead imagery has critical impact to the way we understand our environment and offers crucial information for scene understanding, climate change research, disaster response, urban planning, forest management, and many other applications. At present, deep learning is increasingly used in remote sensing, but mostly borrowing algorithms developed for natural images in the computer vision community. Specific challenges arise while applying deep learning to remote sensing. These challenges include issues related to the high dimensionality and limited labeled data, security and robustness to adversarial attacks, and model generalization. In this Thesis we focus on tackling these key challenges. …