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Li, Z
Li, L
Luck, B
Levi, O
Lesueur, C
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Authors
Cohen, Y
Alchanatis, V
Levi, O
Cohen, S
Xu, X
Li, Z
Yang, G
Gu, X
Song, X
Yang, X
Feng, H
Luck, B
Drewry, J
Chassen, E
Steffan, S
Fassinou Hotegni, N
Karangwa, A
Manyatsi, A
Frimpong, K.A
Amri, M
Cammarano, D
Lesueur, C
Taylor, J
Phillips, S
Achigan-Dako, E
Tasissa, A
Li, L
Murphy, J.M
Topics
Machine Vision / Multispectral & Hyperspectral Imaging Applications to Precision Agriculture
Proximal and Remote Sensing of Soil and Crop (including Phenotyping)
Applications of Unmanned Aerial Systems
Country Representative Report
Artificial Intelligence (AI) in Agriculture
Type
Poster
Oral
Year
2012
2018
2024
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Filter results5 paper(s) found.

1. A Method for Combining Spatial and Hyperspectral Information for Delineation of Homogenous Management Zones

Hyperspectral (HS) remote sensing is a constantly developing field. New remote sensing applications of different fields constantly appear. The possibility of acquisition information about an object without physical contact is spanning new opportunities in many fields and for precision agricultural in particular. These opportunities demand constant improvement and development of new analysis approaches and algorithms,... Y. Cohen, V. Alchanatis, O. Levi, S. Cohen

2. Using Canopy Hyperspectral Measurements to Evaluate Nitrogen Status in Different Leaf Layers of Winter Wheat

Nitrogen (N) is one of the most important nutrient matters for crop growth and has the marked influence on the ultimate formation of yield and quality in crop production. As the most mobile nutrient constituent, N always transfers from the bottom to top leaves under N stress condition. Vertical gradient changes of leaf N concentration are a general feature in canopies of crops. Hence, it is significant to effectively acquire vertical N information for optimizing N fertilization managements.... X. Xu, Z. Li, G. Yang, X. Gu, X. Song, X. Yang, H. Feng

3. Unmanned Aerial Systems and Remote Sensing for Cranberry Production

Wisconsin is the largest producer of Cranberries in the United States with 5.6 million barrels produced in 2017. To date, Precision Agriculture technologies adapted to cranberry production have been limited. The objective of this research was to assess the feasibility of the use of commercial remote sensing devices and Unmanned Aerial Systems in cranberry production. Two commercially available sensors were assessed for use in cranberry production: 1) MicaSense Red Edge and 2) Zenmuse XT. Initial... B. Luck, J. Drewry, E. Chassen, S. Steffan

4. Capacity Building of African Young Scientists in Precision Agriculture Through Cross-regional Academic Mobility for Enhanced Climate-smart Agri-food System: an Intra Africa Mobility Project on Precision Agriculture

Climate change is one of the main problems affecting food and nutrition globally, particularly in sub-Saharan Africa. Adapting to and/or mitigating climate change in the agri-food sector requires merging information technologies, genetic innovations, and sustainable farming practices to empower the agricultural youth sector to create effective and locally adapted solutions. Precision Agriculture applied to crops (PAAC), has been advocated as a strategic solution to mitigate/adapt agriculture at... N. Fassinou hotegni, A. Karangwa, A. Manyatsi, K.A. Frimpong, M. Amri, D. Cammarano, C. Lesueur, J. Taylor, S. Phillips, E. Achigan-dako

5. 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