Zobrazeno 1 - 7
of 7
pro vyhledávání: '"B. S. Bennedsen"'
Identifying Apple Surface Defects Using Principal Components Analysis and Artificial Neural Networks
Publikováno v:
Transactions of the ASABE. 50:2257-2265
Artificial neural networks and principal components were used to detect surface defects on apples in near-infrared images. Neural networks were trained and tested on sets of principal components, derived from columns of pixels from images of apples a
Publikováno v:
Computers and Electronics in Agriculture. 48:92-102
An experimental machine vision system was used to identify surface defects on apples, including bruises. Images were captured through two optical filters at 740 and 950nm, respectively. In the ensuing grey scale images, defects appeared as dark areas
Autor:
D. L. Peterson, B. S. Bennedsen
Publikováno v:
Applied Engineering in Agriculture. 21:31-34
This research studied the performance of the ARS fruit-harvesting concept in relationship to apple removal efficiency and damage. There were no differences in apple removal efficiency or fruit quality between a single impulse or three rapid impulses
Autor:
B. S. Bennedsen, D. L. Peterson
Publikováno v:
Transactions of the ASAE. 48:1819-1826
Spectral reflection in the wavebands between 600 and 1100 nm was tested for its ability to classify apples according to the presence of watercore and mealiness. A model developed by partial least squares (PLS) regression using four, 10 nm wide waveba
Autor:
B. S. Bennedsen, H. Moth-Poulsen
Publikováno v:
Acta Horticulturae. :83-89
The objective of the research was to establish, whether it would be possible to train an automatic system to predict the final quality of a pot plant, based on features measured on half-grown plants. Pot roses and Hibiscus plants were used. Images we
Autor:
B. S. Bennedsen, L. Kohsel
Publikováno v:
Acta Horticulturae. :273-283
In Denmark, ornamental products are graded by manual labour. The task is very demanding regarding labour and training of the employees. This paper addresses the characteristics of manual grading of pot-roses, with its variance and bias of plant evalu
Publikováno v:
Transactions of the ASAE. 42:871-876
A unique robotic bulk harvester was conceived and developed to remove apples grown on narrow inclined trellises. The system combined mechanical harvesting technology with sensors and intelligent adaptive technology to identify an individual branch, d