乐胖代购免代理版

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However, most previous works require fast and constant\u2010time weed detection systems to achieve real\u2010time treatment, which forecloses the implementation of more capable but time\u2010consuming algorithms, for example, learning\u2010based methods. In this paper, a nonoverlapping multicamera system is applied to provide flexibility for the weed control system in dealing with the indeterminate classification delays. The design, implementation, and testing of our proposed modular weed control unit with mechanical and chemical weeding tools are presented. A framework that performs naive Bayes filtering, 3D direct intra\u2010 and inter\u2010camera visual tracking, and predictive control, while integrating state\u2010of\u2010the\u2010art crop\/weed detection algorithms, is developed to guide the tools to achieve high\u2010precision weed removal. 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