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Tasissa, A
Choi, J
M. Rabello, L
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Authors
M. Rabello, L
R. D. Pereira, R
C. Lopes, W
Y. Inamasu, R
V. de Sousa, R
Sung, N
Chung, S
Kim, Y
han, K
Choi, J
Kim, J
Cho, Y
Jang, S
Tasissa, A
Lichtenberg,, S
Tasissa, A
Li, L
Murphy, J.M
Topics
Engineering Technologies and Advances
Engineering Technologies and Advances
Wireless Sensor Networks and Farm Connectivity
Artificial Intelligence (AI) in Agriculture
Type
Poster
Oral
Year
2012
2016
2024
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Filter results4 paper(s) found.

1. Implementation of a Controller Unit Based on the ISO 11783 Standard for Automatic Measurement of the Electrical Conductivity of the Soil

... L. M. rabello, R. R. d. pereira, W. C. lopes, R. Y. inamasu, R. V. de sousa

2. Evaluation of a Sensor and Control Interface Module for Monitoring of Greenhouse Environment

Protected horticulture in greenhouses and plant factories has been increased in many countries due to the advantages of year-round production in controlled environment for improved productivity and quality. For protected horticulture, environmental conditions are monitored and controlled through wired and wireless devices. Various devices are used for monitoring and control of spatial and temporal variability in crop growth environmental conditions. Recently, various sensors and control devices,... N. Sung, S. Chung, Y. Kim, K. Han, J. Choi, J. Kim, Y. Cho, S. Jang

3. 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,

4. 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