Proceedings
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| Filter results2 paper(s) found. |
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1. Quantifying Boom Movement in Agricultural Sprayer Booms Using Neural Networks for Real-world Field ScenariosApplication rate errors in self-propelled agricultural sprayers remain a significant concern, necessitating a comprehensive understanding of boom movement during actual field operating scenarios. This study introduces new objectives to quantify boom movement across commercial sprayers when operated by different individuals and compares these movements among various machines. The goal is to develop a metric that identifies potential improvement needs for boom height control system. The approach... T. Kaloya, A. Sharda, A. Dalal |
2. Utilizing Image-based Artificial Intelligence for Grading Bovine OocytesFor years, proper oocyte selection has been carried out with the precision of a lab technician’s eyes. The classification of oocytes using image-based artificial intelligence is a new technology that IVF lab technicians, cattle genetics companies, and veterinarians can utilize. Via the aspiration of the follicles on a cow’s ovaries, oocytes are able to be collected. Once oocytes are obtained from the ovaries of a cow, they are sent to an IVF lab to be cleaned and evaluated by a lab... G. Koppelman, J.P. Fulton, S. Khanal, T. Berger-wolf |