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David J Lary

Showing results (11-20 of 22) with videos related to

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Environmental Monitoring and Assessment|June 30, 2019
Applying machine learning to forecast daily Ambrosia pollen using environmental and NEXRAD parametersGebreab K Zewdie, Xun Liu, Daji Wu, et al.
Sensors (Basel, Switzerland)|December 28, 2019
Using Machine Learning for the Calibration of Airborne Particulate SensorsLakitha O H Wijeratne, Daniel R Kiv, Adam R Aker, et al.
Frontiers in Plant Science|March 7, 2017
<i>Phytophthora megakarya</i> and <i>P. palmivora</i>, Causal Agents of Black Pod Rot, Induce Similar Plant Defense Responses Late during Infection of Susceptible Cacao PodsShahin S Ali, Jonathan Shao, David J Lary, et al.
Geospatial Health|January 21, 2015
Estimating the global abundance of ground level presence of particulate matter (PM2.5)David J Lary, Fazlay S Faruque, Nabin Malakar, et al.
Environmental Health Insights|May 5, 2017
Using machine learning to estimate atmospheric <i>Ambrosia</i> pollen concentrations in Tulsa, OKXun Liu, Daji Wu, Gebreab K Zewdie, et al.
Environmental Monitoring and Assessment|June 30, 2019
Time-series analysis of satellite-derived fine particulate matter pollution and asthma morbidity in Jackson, MSHoward H Chang, Anqi Pan, David J Lary, et al.
Sensors (Basel, Switzerland)|March 17, 2025
Calibration of Low-Cost LoRaWAN-Based IoT Air Quality Monitors Using the Super Learner Ensemble: A Case Study for Accurate Particulate Matter MeasurementGokul Balagopal, Lakitha Wijeratne, John Waczak, et al.
Global Advances in Health and Medicine|March 3, 2018
Advanced Metrics for Assessing Holistic Care: The "Epidaurus 2" ProjectFrederick O Foote, Herbert Benson, Ann Berger, et al.
Sensors (Basel, Switzerland)|June 10, 2022
Decoding Physical and Cognitive Impacts of Particulate Matter Concentrations at Ultra-Fine ScalesShawhin Talebi, David J Lary, Lakitha O H Wijeratne, et al.
Sensors (Basel, Switzerland)|April 3, 2021
Autonomous Learning of New Environments with a Robotic Team Employing Hyper-Spectral Remote Sensing, Comprehensive In-Situ Sensing and Machine LearningDavid J Lary, David Schaefer, John Waczak, et al.
Pageof 3

Showing results (11-20 of 22) with videos related to

Sort By:
Pageof 3
Environmental Monitoring and Assessment|June 30, 2019
Applying machine learning to forecast daily Ambrosia pollen using environmental and NEXRAD parametersGebreab K Zewdie, Xun Liu, Daji Wu, et al.
Sensors (Basel, Switzerland)|December 28, 2019
Using Machine Learning for the Calibration of Airborne Particulate SensorsLakitha O H Wijeratne, Daniel R Kiv, Adam R Aker, et al.
Frontiers in Plant Science|March 7, 2017
<i>Phytophthora megakarya</i> and <i>P. palmivora</i>, Causal Agents of Black Pod Rot, Induce Similar Plant Defense Responses Late during Infection of Susceptible Cacao PodsShahin S Ali, Jonathan Shao, David J Lary, et al.
Geospatial Health|January 21, 2015
Estimating the global abundance of ground level presence of particulate matter (PM2.5)David J Lary, Fazlay S Faruque, Nabin Malakar, et al.
Environmental Health Insights|May 5, 2017
Using machine learning to estimate atmospheric <i>Ambrosia</i> pollen concentrations in Tulsa, OKXun Liu, Daji Wu, Gebreab K Zewdie, et al.
Environmental Monitoring and Assessment|June 30, 2019
Time-series analysis of satellite-derived fine particulate matter pollution and asthma morbidity in Jackson, MSHoward H Chang, Anqi Pan, David J Lary, et al.
Sensors (Basel, Switzerland)|March 17, 2025
Calibration of Low-Cost LoRaWAN-Based IoT Air Quality Monitors Using the Super Learner Ensemble: A Case Study for Accurate Particulate Matter MeasurementGokul Balagopal, Lakitha Wijeratne, John Waczak, et al.
Global Advances in Health and Medicine|March 3, 2018
Advanced Metrics for Assessing Holistic Care: The "Epidaurus 2" ProjectFrederick O Foote, Herbert Benson, Ann Berger, et al.
Sensors (Basel, Switzerland)|June 10, 2022
Decoding Physical and Cognitive Impacts of Particulate Matter Concentrations at Ultra-Fine ScalesShawhin Talebi, David J Lary, Lakitha O H Wijeratne, et al.
Sensors (Basel, Switzerland)|April 3, 2021
Autonomous Learning of New Environments with a Robotic Team Employing Hyper-Spectral Remote Sensing, Comprehensive In-Situ Sensing and Machine LearningDavid J Lary, David Schaefer, John Waczak, et al.
Pageof 3