نتایج جستجو برای: invasive weed algorithm
تعداد نتایج: 904760 فیلتر نتایج به سال:
in order to study the phonological stages and growth period of invasive weed ranunculus ficaria based on degree days and to study the effect of planting depth on sprouting the tubers roots of this weed, two separate experiments were conducted in crd with 5 replications at ferdwosi university of mashhad in 2008. in the first study germinated tubers were planted in 5 cm depth and the observations...
A system to estimate the weed density between two rows of soybeans was developed. An environmentally adaptive segmentation algorithm (EASA) was used to segment the plants from the background of the image. The effect of two image data transformations on the segmentation performance of the EASA was investigated, and the RGB-IV1V2 transformation resulted in significantly higher quality segmentatio...
abstract- a real-time, site-specific, machine-vision based, inter-row patch herbicide application system was developed and evaluated. the image resolution was 640 × 480 pixels covering a total area of 350 mm x 240 mm of a field composed of four quadrants of 350 mm x 60 mm each. the image frames were processed by labview® and matlab®. the developed algorithm, based on weed coverage ratio and seg...
Roger L. Sheley U.S. Department of Agriculture–Agricultural Research Service, 67826-A Highway 205, Burns, OR 97720 The impact of invasive weed management on plant community composition is highly dependent on location-specific factors. Therefore, treatment means from experiments conducted at a given set of locations will not reliably predict community response to weed management elsewhere. We de...
Clustering is an unsupervised learning method that is used to group similar objects. One of the most popular and efficient clustering methods is K-means, as it has linear time complexity and is simple to implement. However, it suffers from gets trapped in local optima. Therefore, many methods have been produced by hybridizing K-means and other methods. In this paper, we propose a hybrid method ...
Climate change may exacerbate the impacts of plant invasions by providing opportunities for new naturalisations and for alien species to expand into regions where previously they could not survive and reproduce. Although climate change is not expected to favour invasive plants in every case, in Aotearoa-New Zealand a large pool of potential new weeds already exists and this country is predicted...
1. Parameter uncertainty challenges the use of matrix models because it violates key assumptions underlying elasticity analyses. We have developed a matrix model to compare Monte Carlo methods with elasticity analyses for estimation of the relative importance of factors in the asymptotic population growth rate, λ, of Cirsium vulgare (spear thistle) in Nebraska, USA. 2. We calculated λ for a bas...
More than half of the Australian cropping land is no-tillage and weed control within continuous no-tillage agricultural cropping area is becoming more and more difficult. A major problem is that the heavy herbicide usage causes some of more prolific weeds becoming more resistant to the regular herbicides and therefore more powerful and more expensive options are being pursued. To overcome such ...
Weed detection using image processing is a progressive research area which can revolutionize crop production and increase efficiency in herbicide usage. A SVM classifier was applied in our research to classify and to detect the weed type for weed scouting and spot weeding purposes. However, parameter fine tuning and feature selection for SVM is a complex procedure that is still an active area o...
In order to reduce herbicide application an intelligent sprayer boom is being developed. It only sprays with herbicides if the weed infestation exceeds a certain weed control threshold. The estimation of leaf cover of weeds through image analysis is a prerequisite for the weed management model of the intelligent sprayer boom. Destructive and human perception methods of leaf cover estimation are...
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