Proceedings

Find matching any: Reset
Tasissa, A
Thompson, L.J
Add filter to result:
Authors
Thompson, L.J
Tasissa, A
Lichtenberg,, S
Tasissa, A
Li, L
Murphy, J.M
Topics
In-Season Nitrogen Management
Wireless Sensor Networks and Farm Connectivity
Artificial Intelligence (AI) in Agriculture
Type
Poster
Oral
Year
2018
2024
Home » Authors » Results

Authors

Filter results3 paper(s) found.

1. Using Drone Based Sensors to Direct Variable-Rate, In-Season, Aerial Nitrogen Application on Corn

Improving nutrient management on farms is a critical issue nationwide. Applying a portion of N fertilizer during the growing season, alongside the growing corn crop is one way to improve nitrogen management. Sidedress N applications allow the availability of N fertilizer to more closely match the time when the crop is rapidly uptaking N. Additionally, waiting to apply a portion of the N during the growing season allows for management which is responsive to current growing season conditions. Crop... L.J. Thompson

2. Nystrom-based Localization in Precision Agriculture Sensors

Wireless sensor networks play a pivotal role in a myriad of applications, ranging from agriculture and health monitoring and to tracking and structural health monitoring. One crucial aspect of these applications involves accurately determining the positions of the sensors. In this study, we study a novel Nystrom-based sampling protocol in which a selected group of anchor nodes, with known locations, establish communication with only a subset of the remaining sensor nodes. Leveraging partial distance... A. Tasissa, S. Lichtenberg,

3. Sparse Coding for Classification Via a Locality Regularizer: with Applications to Agriculture

High-dimensional data is commonly encountered in various applications, including genomics, as well as image and video processing. Analyzing, computing, and visualizing such data pose significant challenges. Feature extraction methods become crucial in addressing these challenges by obtaining compressed representations that are suitable for analysis and downstream tasks. One effective technique along these lines is sparse coding, which involves representing data as a sparse linear combination of... A. Tasissa, L. Li, J.M. Murphy