- Patent Title: Detection and management of target vegetation using machine vision
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Application No.: US16757159Application Date: 2018-11-02
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Publication No.: US11468670B2Publication Date: 2022-10-11
- Inventor: Arnold W. Schumann , Nathan S. Boyd , Jialin Yu
- Applicant: University of Florida Research Foundation, Inc.
- Applicant Address: US FL Gainesville
- Assignee: University of Florida Research Foundation, Inc.
- Current Assignee: University of Florida Research Foundation, Inc.
- Current Assignee Address: US FL Gainesville
- Agency: Thomas | Horstemeyer, LLP
- International Application: PCT/US2018/058829 WO 20181102
- International Announcement: WO2019/094266 WO 20190516
- Main IPC: A01M7/00
- IPC: A01M7/00 ; G06V20/10 ; G06T7/70 ; G06N20/00 ; A01M21/04

Abstract:
Various embodiments detect and manage target vegetation in vegetation areas, including crop beds, between crop beds, and turfgrasses. In one embodiment, a machine learning model is trained to detect target vegetation in captured images. An information processing system is programmed utilizing the machine learning model. One or more images of a particular area are captured, and target vegetation is detected within the one or more images. A position of the detected target vegetation is determined within the one or more images. An applicator disposed on an agrochemical applicator system that is mapped to the position of the detected target vegetation within the one or more images is determined. The applicator is activated based on a current speed of a vehicle coupled to the agrochemical applicator system, and further based on configuration data associated with the applicator. Activating the applicator selectively applies an agrochemical to the detected target vegetation.
Public/Granted literature
- US20200342225A1 Detection and Management of Target Vegetation Using Machine Vision Public/Granted day:2020-10-29
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