Proceedings :: International Society of Precision Agriculture

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Lotfi, A

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Authors

Nketia, K

Lotfi, A

Neudorf, S

Ha, T

Khan, A

Otterson, J

Lotfi, A

Shirtliffe, S

Carter, A

Ha, T

Eramian, M

Neupane, S

Topics

UAV-Based Scouting, Imaging, and Targeted Applications

Predictive Modeling, Phenotyping, and Digital Tools for Decision Support

Type

Oral

Year

2026

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Filter results2 paper(s) found.
1. Autonomous Edge-AI–Enabled Drone Systems for Real-Time Agricultural Inference and Decision-Making High-throughput, low-latency phenotyping and field surveillance remain critical bottlenecks in precision agriculture and environmental monitoring due to delayed data turnaround, large data volumes, computationally intensive preprocessing, and expertise-heavy analysis workflows. These constraints hinder timely crop improvement, pest and disease management, and informed agronomic decision-making. To address these challenges, we present an integrated, end-to-end autonomous drone system that enables...
2. Semi-Automatic Plot Segmentation for Crop Phenotyping Using Adaptive Spectral Indices and SAM3 Yield trials and hill plots are widely used in plant breeding to evaluate large numbers of genotypes simultaneously. Extracting per-plot canopy boundaries from drone imagery is a key step in this process, but manual delineation is time-consuming, and rigid grid overlays do not account for true canopy boundaries. This paper presents an annotation-free pipeline for segmenting individual plots from multispectral drone imagery, requiring only approximate plot dimensions as input. The pipeline first... A. Lotfi, S. Shirtliffe, A. Carter, T. Ha, M. Eramian, S. Neupane

Filter results2 paper(s) found.

1. Autonomous Edge-AI–Enabled Drone Systems for Real-Time Agricultural Inference and Decision-Making

High-throughput, low-latency phenotyping and field surveillance remain critical bottlenecks in precision agriculture and environmental monitoring due to delayed data turnaround, large data volumes, computationally intensive preprocessing, and expertise-heavy analysis workflows. These constraints hinder timely crop improvement, pest and disease management, and informed agronomic decision-making. To address these challenges, we present an integrated, end-to-end autonomous drone system that enables...

2. Semi-Automatic Plot Segmentation for Crop Phenotyping Using Adaptive Spectral Indices and SAM3

Yield trials and hill plots are widely used in plant breeding to evaluate large numbers of genotypes simultaneously. Extracting per-plot canopy boundaries from drone imagery is a key step in this process, but manual delineation is time-consuming, and rigid grid overlays do not account for true canopy boundaries. This paper presents an annotation-free pipeline for segmenting individual plots from multispectral drone imagery, requiring only approximate plot dimensions as input. The pipeline first... A. Lotfi, S. Shirtliffe, A. Carter, T. Ha, M. Eramian, S. Neupane