Zobrazeno 1 - 10
of 102
pro vyhledávání: '"Glen C. Rains"'
Autor:
Shekhar Thapa, Glen C. Rains, Wesley M. Porter, Guoyu Lu, Xianqiao Wang, Canicius Mwitta, Simerjeet S. Virk
Publikováno v:
AgriEngineering, Vol 6, Iss 1, Pp 803-822 (2024)
Several studies on robotic cotton harvesters have designed their end-effectors and harvesting algorithms based on the approach of harvesting a single cotton boll at a time. These robotic cotton harvesting systems often have slow harvesting times per
Externí odkaz:
https://doaj.org/article/bffb71786a7349d0afd8b641539b4ffe
Publikováno v:
Frontiers in Agronomy, Vol 6 (2024)
Small autonomous robotic platforms can be utilized in agricultural environments to target weeds in their early stages of growth and eliminate them. Autonomous solutions reduce the need for labor, cut costs, and enhance productivity. To eliminate the
Externí odkaz:
https://doaj.org/article/d42d4ccdb647438386ee760bd430f773
Autor:
Canicius Mwitta, Glen C. Rains
Publikováno v:
Frontiers in Robotics and AI, Vol 11 (2024)
Autonomous navigation in agricultural fields presents a unique challenge due to the unpredictable outdoor environment. Various approaches have been explored to tackle this task, each with its own set of challenges. These include GPS guidance, which f
Externí odkaz:
https://doaj.org/article/3db7520a4b02495aadbc3336b0c85215
Publikováno v:
Sensors, Vol 24, Iss 3, p 970 (2024)
In this paper, we present the development of a low-cost distributed computing pipeline for cotton plant phenotyping using Raspberry Pi, Hadoop, and deep learning. Specifically, we use a cluster of several Raspberry Pis in a primary-replica distribute
Externí odkaz:
https://doaj.org/article/c172eb3ba56b4dab98c97ee941e8e797
Publikováno v:
Sensors, Vol 24, Iss 2, p 514 (2024)
The knowledge that precision weed control in agricultural fields can reduce waste and increase productivity has led to research into autonomous machines capable of detecting and removing weeds in real time. One of the driving factors for weed detecti
Externí odkaz:
https://doaj.org/article/25722c5df28347798456c7442e2f816c
Autor:
Chinmay U. Parab, Canicius Mwitta, Miller Hayes, Jason M. Schmidt, David Riley, Kadeghe Fue, Suchendra Bhandarkar, Glen C. Rains
Publikováno v:
AgriEngineering, Vol 4, Iss 2, Pp 507-522 (2022)
In this study, we have compared YOLOv4, a single-shot detector to Faster-RCNN, a two-shot detector to detect and classify whiteflies on yellow-sticky tape (YST). An IoT remote whitefly monitoring station was developed and placed in a whitefly rearing
Externí odkaz:
https://doaj.org/article/1808611f493743dfbccfd531f313d2b6
Autor:
Denis O. Kiobia, Canicius J. Mwitta, Kadeghe G. Fue, Jason M. Schmidt, David G. Riley, Glen C. Rains
Publikováno v:
Sensors, Vol 23, Iss 8, p 4127 (2023)
Using artificial intelligence (AI) and the IoT (Internet of Things) is a primary focus of applied engineering research to improve agricultural efficiency. This review paper summarizes the engagement of artificial intelligence models and IoT technique
Externí odkaz:
https://doaj.org/article/5ea4c5bf34054c6e8bf762e9293ee217
An Extensive Review of Mobile Agricultural Robotics for Field Operations: Focus on Cotton Harvesting
Publikováno v:
AgriEngineering, Vol 2, Iss 1, Pp 150-174 (2020)
In this review, we examine opportunities and challenges for 21st-century robotic agricultural cotton harvesting research and commercial development. The paper reviews opportunities present in the agricultural robotics industry, and a detailed analysi
Externí odkaz:
https://doaj.org/article/5a95991a1be44474b2e3a9ef431fbb1f
Publikováno v:
Agronomy, Vol 12, Iss 11, p 2681 (2022)
Herbicides have been the primary weed management practice in agriculture for decades. However, due to their effects on the environment in addition to weeds becoming resistant, alternative approaches to weed control are critical. One approach is using
Externí odkaz:
https://doaj.org/article/2b0dc618b16c4282a4261d4bcd21e10f
Publikováno v:
Remote Sensing, Vol 12, Iss 2, p 315 (2020)
Improving plant photosynthesis provides the best possibility for increasing crop yield potential, which is considered a crucial effort for global food security. Chlorophyll fluorescence is an important indicator for the study of plant photosynthesis.
Externí odkaz:
https://doaj.org/article/755118dedfa44200a499e12055b60072