Search Results - "Lary, David J"

Cloud Detection Using an Ensemble of Pixel-Based Machine Learning Models Incorporating Unsupervised Classification by Yu, Xiaohe, Lary, David J.

“…Remote sensing imagery, such as that provided by the United States Geological Survey (USGS) Landsat satellites, has been widely used to study environmental…”
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Remote Sensing of CDOM, CDOM Spectral Slope, and Dissolved Organic Carbon in the Global Ocean by Aurin, Dirk, Mannino, Antonio, Lary, David J.

“…A Global Ocean Carbon Algorithm Database (GOCAD) has been developed from over 500 oceanographic field campaigns conducted worldwide over the past 30 years…”
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Data-Driven EEG Band Discovery with Decision Trees by Talebi, Shawhin, Waczak, John, Fernando, Bharana A, Sridhar, Arjun, Lary, David J

“…Electroencephalography (EEG) is a brain imaging technique in which electrodes are placed on the scalp. EEG signals are commonly decomposed into frequency bands…”
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Using Machine Learning for the Calibration of Airborne Particulate Sensors by Wijeratne, Lakitha O H, Kiv, Daniel R, Aker, Adam R, Talebi, Shawhin, Lary, David J

“…Airborne particulates are of particular significance for their human health impacts and their roles in both atmospheric radiative transfer and atmospheric…”
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PM2.5 Modeling and Historical Reconstruction over the Continental USA Utilizing GOES-16 AOD by Yu, Xiaohe, Lary, David J., Simmons, Christopher S.

“…In this study, we present a nationwide machine learning model for hourly PM2.5 estimation for the continental United States (US) using high temporal resolution…”
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Machine Learning for Light Sensor Calibration by Zhang, Yichao, Wijeratne, Lakitha O. H., Talebi, Shawhin, Lary, David J.

“…Sunlight incident on the Earth’s atmosphere is essential for life, and it is the driving force of a host of photo-chemical and environmental processes, such as…”
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Unsupervised Characterization of Water Composition with UAV-Based Hyperspectral Imaging and Generative Topographic Mapping by Waczak, John, Aker, Adam, Wijeratne, Lakitha O. H., Talebi, Shawhin, Fernando, Ashen, Dewage, Prabuddha M. H., Iqbal, Mazhar, Lary, Matthew, Schaefer, David, Balagopal, Gokul, Lary, David J.

“…Unmanned aerial vehicles equipped with hyperspectral imagers have emerged as an essential technology for the characterization of inland water bodies. The high…”
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Decoding Physical and Cognitive Impacts of Particulate Matter Concentrations at Ultra-Fine Scales by Talebi, Shawhin, Lary, David J, Wijeratne, Lakitha O H, Fernando, Bharana, Lary, Tatiana, Lary, Matthew, Sadler, John, Sridhar, Arjun, Waczak, John, Aker, Adam, Zhang, Yichao

“…The human body is an incredible and complex sensing system. Environmental factors trigger a wide range of automatic neurophysiological responses. Biometric…”
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High Spatial-Temporal PM2.5 Modeling Utilizing Next Generation Weather Radar (NEXRAD) as a Supplementary Weather Source by Yu, Xiaohe, Lary, David J., Simmons, Christopher S., Wijeratne, Lakitha O. H.

“…PM2.5, a type of fine particulate with a diameter equal to or less than 2.5 micrometers, has been identified as a major source of air pollution, and is…”
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Characterizing Water Composition with an Autonomous Robotic Team Employing Comprehensive In Situ Sensing, Hyperspectral Imaging, Machine Learning, and Conformal Prediction by Waczak, John, Aker, Adam, Wijeratne, Lakitha O. H., Talebi, Shawhin, Fernando, Ashen, Dewage, Prabuddha M. H., Iqbal, Mazhar, Lary, Matthew, Schaefer, David, Lary, David J.

“…Inland waters pose a unique challenge for water quality monitoring by remote sensing techniques due to their complicated spectral features and small-scale…”
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Providing Fine Temporal and Spatial Resolution Analyses of Airborne Particulate Matter Utilizing Complimentary In Situ IoT Sensor Network and Remote Sensing Approaches by Dewage, Prabuddha M. H., Wijeratne, Lakitha O. H., Yu, Xiaohe, Iqbal, Mazhar, Balagopal, Gokul, Waczak, John, Fernando, Ashen, Lary, Matthew D., Ruwali, Shisir, Lary, David J.

“…This study aims to provide analyses of the levels of airborne particulate matter (PM) using a two-pronged approach that combines data from in situ Internet of…”
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Autonomous Learning of New Environments with a Robotic Team Employing Hyper-Spectral Remote Sensing, Comprehensive In-Situ Sensing and Machine Learning by Lary, David J, Schaefer, David, Waczak, John, Aker, Adam, Barbosa, Aaron, Wijeratne, Lakitha O H, Talebi, Shawhin, Fernando, Bharana, Sadler, John, Lary, Tatiana, Lary, Matthew D

“…This paper describes and demonstrates an autonomous robotic team that can rapidly learn the characteristics of environments that it has never seen before. The…”
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Low Power Greenhouse Gas Sensors for Unmanned Aerial Vehicles by Khan, Amir, Schaefer, David, Tao, Lei, Miller, David J., Sun, Kang, Zondlo, Mark A., Harrison, William A., Roscoe, Bryan, Lary, David J.

“…We demonstrate compact, low power, lightweight laser-based sensors for measuring trace gas species in the atmosphere designed specifically for electronic…”
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Estimating the global abundance of ground level presence of particulate matter (PM2.5) by Lary, David J, Faruque, Fazlay S, Malakar, Nabin, Moore, Alex, Roscoe, Bryan, Adams, Zachary L, Eggelston, York

“…With the increasing awareness of the health impacts of particulate matter, there is a growing need to comprehend the spatial and temporal variations of the…”
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Using Remote Control Aerial Vehicles to Study Variability of Airborne Particulates by Harrison, William A., Lary, David J., Nathan, Brian J., Moore, Alec G.

“…Airborne particulates play a significant role in the atmospheric radiative balance and impact human health. To characterize this impact, global-scale…”
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Using machine learning to understand the temporal morphology of the PM2.5 annual cycle in East Asia by Wu, Daji, Lary, David J., Zewdie, Gebreab K., Liu, Xun

“…PM 2.5 air pollution is a significant issue for human health all over the world, especially in East Asia. A large number of ground-based measurement sites have…”
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Applying Deep Neural Networks and Ensemble Machine Learning Methods to Forecast Airborne Ambrosia Pollen by Zewdie, Gebreab K, Lary, David J, Levetin, Estelle, Garuma, Gemechu F

“…Allergies to airborne pollen are a significant issue affecting millions of Americans. Consequently, accurately predicting the daily concentration of airborne…”
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Combining domain filling with a self-organizing map to analyze multi-species hydrocarbon signatures on a regional scale by Nathan, Brian J., Lary, David J.

“…For the period of the Barnett Coordinated Campaign, October 16–31, 2013, hourly concentrations for 46 volatile organic compounds (VOCs) were recorded at 14 air…”
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Estimating the daily pollen concentration in the atmosphere using machine learning and NEXRAD weather radar data by Zewdie, Gebreab K., Lary, David J., Liu, Xun, Wu, Daji, Levetin, Estelle

“…Millions of people have an allergic reaction to pollen. The impact of pollen allergies is on the rise due to increased pollen levels caused by global warming…”
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Machine Learning for Estimating Electron Transfer Rates From Square Wave Voltammetry by Adams, Austen C., Jha, Sauraj, Lary, David J., Slinker, Jason D.

“…Electrochemistry of surface‐bound molecules is of high importance for numerous electronic and sensor applications. Extracting the electron transfer rate is…”
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