Proceedings
Authors
| Filter results3 paper(s) found. |
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1. Rapid Assessment of Yield Using Machine Learning Models and UAV Multispectral Imagery for Soybean Breeding PlotsAdvances in precision agriculture in data collection, crop monitoring, screening, and management over the 10-15 years are revolutionizing on-farm agricultural research trials. In crop breeding plots, this approach is called "High Throughput Phenotyping", which uses innovative technology to extract phenotypic data for large populations. Remote sensing has become one of the commonly used platforms for rapid acquisition of imagery data at spatial and temporal scale. Particularly, the unmanned... A. Dua, A. Sharda, W. Schapaugh, R. Hessel, S. Rai |
2. Enhancing Seeding Efficiency: Evaluating Row Cleaners with Computer Vision in Precision AgricultureIn precision agriculture, the effective sowing of seeds is crucial but often hindered by challenges like hair pinning, low soil temperatures, and heavy residue on the soil surface. To address these issues, row cleaners are employed to clear the path for seeder opener discs, ensuring a clean, uniform trench for seed placement. This study examines the performance of various row cleaner models and introduces a novel method for their automatic, quantitative evaluation using computer vision technology. We... F. Sidharth, A. Sharda, B.G. Berretta |
3. Row-unit Integrated Multi-camera Edge AI System for Real-time Small-grain Seeding Performance Data CollectionHigh-quality synchronized imagery collected under field conditions is a limiting factor in the development of computer vision models for small-grain seeding applications. This study presents the design, implementation, and field deployment of a row-unit integrated multi-camera data-acquisition system intended to standardize multi-view data collection during planting. The system mounts directly to a seed-drill row unit and integrates three Power-over-Ethernet (PoE) Basler cameras positioned to... A. Sharda, B. Vail, S. Rai, R. Harsha Chepally |