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Helga, W
Hsieh, S
Huang, Z
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Authors
Cammarano, D
Drexler, D
Hinsinger, P
Martre, P
Draye, X
Sessitsch, A
Pecchioni, N
Cooper, J
Helga, W
Voicu, A
Huang, Z
Lee, W
Takkellapati, N
Hsieh, S
Topics
Big Data, Data Mining and Deep Learning
Artificial Intelligence (AI) in Agriculture
Type
Oral
Poster
Year
2018
2024
2025
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Filter results3 paper(s) found.

1. Shared Protocols and Data Template in Agronomic Trials

Due to the overlap of many disciplines and the availability of novel technologies, modern agriculture has become a wide, interdisciplinary endeavor, especially in Precision Agriculture. The adoption of a standard format for reporting field experiments can help researchers to focus on the data rather than on re-formatting and understanding the structure of the data. This paper describes how a European consortium plans to: i) create a “handbook” of protocols for reporting definitions,... D. Cammarano, D. Drexler, P. Hinsinger, P. Martre, X. Draye, A. Sessitsch, N. Pecchioni, J. Cooper, W. Helga, A. Voicu

2. HOPSY: Harvesting Optimization for Production of Strawberry Using Real-time Detection with YOLOv8

Optimizing the harvesting process presents a continuous challenge within the strawberry industry, especially during peak seasons when precise labor allocation becomes critical for efficiency and cost-effectiveness. The conventional method for addressing this issue has been hindered by an absence of real-time data regarding yield distribution, resulting in less-than-ideal worker assignments and unnecessary expenditures on labor. In response, a novel, portable, real-time strawberry detection system... Z. Huang, W. Lee, N. Takkellapati

3. A Field Machine for Automated Quantification of Sweet Potato Phenotypic Traits

Sweet potato is a globally important food crop, and its breeding is essential for enhancing nutritional value, ensuring food security, and promoting sustainable agriculture. However, the current process of parental selection largely depends on manual visual assessment, which is time-consuming and subject to human bias, thereby limiting both the efficiency and accuracy of breeding programs. In this work, a field machine for automated quantification of sweet potato phenotypic traits was proposed... S. Hsieh