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Raheja, A
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Authors
Bhandari, S
Raheja, A
Chaichi, M.R
Green, R.L
Do, D
Ansari, M
Wolf, J.G
Espinas, A
Pham, F.H
Sherman, T.M
Bhandari, S
Raheja, A
Bhandari, S
Acosta, M
Cordova Gonzalez, C
Raheja, A
Sherafat, A
Topics
Applications of Unmanned Aerial Systems
Applications of Unmanned Aerial Systems
Artificial Intelligence (AI) in Agriculture
Type
Oral
Year
2018
2022
2024
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Filter results3 paper(s) found.

1. Effectiveness of UAV-Based Remote Sensing Techniques in Determining Lettuce Nitrogen and Water Stresses

This paper presents the results of the investigation on the effectiveness of UAV-based remote sensing data in determining lettuce nitrogen and water stresses. Multispectral images of the experimental lettuce plot at Cal Poly Pomona’s Spadra farm were collected from a UAV. Different rows of the lettuce plot were subject to different level of water and nitrogen applications. The UAV data were used in the determination of various vegetation indices. Proximal sensors used for ground-truthing... S. Bhandari, A. Raheja, M.R. Chaichi, R.L. Green, D. Do, M. Ansari, J.G. Wolf, A. Espinas, F.H. Pham, T.M. Sherman

2. Increasing the Accuracy of UAV-Based Remote Sensing Data for Strawberry Nitrogen and Water Stress Detection

This paper presents the methods to increase the accuracy of unmanned aerial vehicles (UAV)-based remote sensing data for the determination of plant nitrogen and water stresses with increased accuracy. As the demand for agricultural products is significantly increasing to keep up with the growing population, it is important to investigate methods to reduce the use of water and chemicals for water conservation, reduction in the production cost, and reduction in environmental impact. UAV-based remote... S. Bhandari, A. Raheja

3. Leveraging UAV-based Hyperspectral Data and Machine Learning Techniques for the Detection of Powderly Mildew in Vineyards

This paper presents the development and validation of machine learning models for the detection of powdery mildew in vineyards. The models are trained and validated using custom datasets obtained from unmanned aerial vehicles (UAVs) equipped with a hyperspectral sensor that can collect images in visible/near-infrared (VNIR) and shortwave infrared (SWIR) wavelengths. The dataset consists of the images of vineyards with marked regions for powdery mildew, meticulously annotated using LabelImg. ... S. Bhandari, M. Acosta, C. Cordova gonzalez, A. Raheja, A. Sherafat