首页|Research from University of Western Ontario in Robotics Provides New Insights (R eal-Time Point Recognition for Seedlings Using Kernel Density Estimators and Pyr amid Histogram of Oriented Gradients)
Research from University of Western Ontario in Robotics Provides New Insights (R eal-Time Point Recognition for Seedlings Using Kernel Density Estimators and Pyr amid Histogram of Oriented Gradients)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-Research findings on robotics are disc ussed in a new report. According to news reporting from London, Canada, by NewsR x journalists, research stated, "This paper introduces a new real-time method ba sed on a combination of kernel density estimators and pyramid histogram of orien ted gradients for identifying a point of interest along the stem of seedlings su itable for stem-stake coupling, also known as the ‘clipping point'." The news correspondents obtained a quote from the research from University of We stern Ontario: "The recognition of a clipping point is a required step for autom ating the stem-stake coupling task, also known as the clipping task, using the r obotic system under development. At present, the completion of this task depends on the expertise of skilled individuals that perform manual clipping. The robot ic stemstake coupling system is designed to emulate human perception (in vision and cognition) for identifying the clipping points and to replicate human motor skills (in dexterity of manipulation) for attaching the clip to the stem at the identified clipping point. The system is expected to clip various types of vege tables, namely peppers, tomatoes, and cucumbers. Our proposed methodology will s erve as a framework for automatic analysis and the understanding of the images o f seedlings for identifying a suitable clipping point."
University of Western OntarioLondonC anadaNorth and Central AmericaEmerging TechnologiesMachine LearningRobot icsRobots
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