David C. Slaughter

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A real-time intelligent robotic weed control system was developed for selective herbicide application to in-row weeds using machine vision and precision chemical application. The robotic vision system took 0.34s to process one image, representing a 11.43 cm by 10.16 cm region of seedline containing 10 plant objects, allowing the prototype robotic weed(More)
In an attempt to find the best electrophysiological indicator of improvement for the neuropathy present in patients with chronic renal failure undergoing hemodialysis, several types of nerve conduction were studied at the beginning of dialysis and six months later. Sural nerve conduction and late response latencies were recorded in addition to conventional(More)
Camera-based 3D reconstruction of physical objects is one of the most popular computer vision trends in recent years. Many systems have been built to model different real-world subjects, but there is lack of a completely robust system for plants. This paper presents a full 3D reconstruction system that incorporates both hardware structures (including the(More)
Active optical sensing (LIDAR and light curtain transmission) devices mounted on a mobile platform can correctly detect, localize, and classify trees. To conduct an evaluation and comparison of the different sensors, an optical encoder wheel was used for vehicle odometry and provided a measurement of the linear displacement of the prototype vehicle along a(More)
authors are solely responsible for the content of this technical presentation. The technical presentation does not necessarily reflect the official position of the American Society of Agricultural and Biological Engineers (ASABE), and its printing and distribution does not constitute an endorsement of views which may be expressed. Technical presentations(More)
This paper demonstrates an automated computer vision system for outdoor tree crop enumeration in a seedling nursery. The complete system incorporates both hardware components (including an embedded microcontroller, an odometry encoder, and an uncalibrated digital color camera) and software algorithms (including microcontroller algorithms and the proposed(More)
This study showed the feasibility of using a hardware-based neural network for increasing processing speed and plant identification rate, however it also indicated that new features needed to be developed for better recognition of tomato plants. With the hardware-based neural network, 38.9% of tomato cotyledons, 37.5% of tomato true leaves, and 85.7% of(More)
Advances in the usage of computer imaging, communication technologies and the successful development of new techniques for precision agriculture have facilitated a smart-digital revolution in row crop agriculture in recent years. The use of a yield monitor, variable rate application (VRA) for fertilizer and herbicides, soil property maps and Global(More)