Proceedings
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| Filter results3 paper(s) found. |
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1. Precision Placement of Corn Gluten Meal for Weed Control in Organic Vegetable ProductionOrganic vegetable producers rank weeds as one of their most troublesome, time consuming, and costly production problems. As a result of the limited number of organically approved weed control herbicides, the precision placement of these materials increases their potential usefulness in organic production systems. As a non-selective preemergence or preplant-incorporated herbicide, corn gluten meal (CGM) inhibits root development; decreases shoot length, and reduces plant survival. The development... C.L. Webber iii, M.J. Taylor, J.W. Shrefler |
2. Using Deep Learning - Convolutional Naural Networks (CNNS) for Real-Time Fruit Detection in the TreeImage/video processing for fruit detection in the tree using hard-coded feature extraction algorithms have shown high accuracy on fruit detection during recent years. While accurate, these approaches even with high-end hardware are still computationally intensive and too slow for real-time systems. This paper details the use of deep convolution neural networks architecture based on single-stage detectors. Using deep-learning techniques eliminates the need for hard-code specific features for specific... K. Bresilla, L. Manfrini, A. Boini, G. Perulli, B. Morandi, L.C. Grappadelli |
3. Use of Precision Technologies to Conduct Successful Within-field, On-farm TrialsPerforming randomized replicated trials in row crop field environments has the potential to increase crop production in environmentally sustainable ways. Successful implementation requires an understanding of implement capabilities and sources of potential systematic error, including operator error. Equipment capabilities can be thought of as a series of several critical “links in a chain,” each with implications that propagate downstream. We will... M. Stelford, A. Krmenec |