Using computer vision to identify seed-borne fungi and other targets associated with common bean seeds based on red–green–blue spectral data

2022 ◽  
Author(s):  
Edson Ampélio Pozza ◽  
Marcelo de Carvalho Alves ◽  
Luciana Sanches
Keyword(s):  
Computer Vision ◽  
Common Bean ◽  
Spectral Data

scholarly journals How does Computer vision compare to standard colorimeter in assessing the seed coat color of common bean (Phaseolus vulgaris L.)?

2019 ◽  
Vol 20 (4) ◽  
pp. 1169-1178
Author(s):  
Filip Varga ◽  
Monika Vidak ◽  
Ksenija Ivanović ◽  
Boris Lazarević ◽  
Ivan Širić ◽  
...  
Keyword(s):  
Computer Vision ◽  
Phaseolus Vulgaris ◽  
Common Bean ◽  
Seed Coat ◽  
Coat Color ◽  
Seed Coat Color ◽  
Phaseolus Vulgaris L

Human Vision and Computer Vision

1985 ◽  
Vol 30 (1) ◽  
pp. 47-47
Author(s):  
Herman Bouma
Keyword(s):  
Computer Vision ◽  
Human Vision

Computer vision for industrial applications

1983 ◽  
Vol 2 (5) ◽  
pp. 130
Author(s):  
J.A. Losty ◽  
P.R. Watkins
Keyword(s):  
Computer Vision ◽  
Industrial Applications

Effects of hydroponic culture system and NaCl on interactions between common bean lines and native rhizobia from Tunisian soils

Agronomie ◽  
2001 ◽  
Vol 21 (6-7) ◽  
pp. 601-605 ◽  
Author(s):  
Moez Jebara ◽  
Jean-Jacques Drevon ◽  
Mohamed Elarbi Aouani
Keyword(s):  
Common Bean ◽  
Culture System ◽  
Hydroponic Culture

The machine training in problems of satellite images’s processing

Metrologiya ◽  
2020 ◽  
pp. 15-37
Author(s):  
L. P. Bass ◽  
Yu. A. Plastinin ◽  
I. Yu. Skryabysheva
Keyword(s):  
Remote Sensing ◽  
Neural Networks ◽  
Computer Vision ◽  
Satellite Images ◽  
Vision Systems ◽  
Earth Remote Sensing ◽  
Practical Applications ◽  
Convolution Neural Networks ◽  
Computer Vision Systems ◽  
Trained Neural Network

Use of the technical (computer) vision systems for Earth remote sensing is considered. An overview of software and hardware used in computer vision systems for processing satellite images is submitted. Algorithmic methods of the data processing with use of the trained neural network are described. Examples of the algorithmic processing of satellite images by means of artificial convolution neural networks are given. Ways of accuracy increase of satellite images recognition are defined. Practical applications of convolution neural networks onboard microsatellites for Earth remote sensing are presented.

Modern Technology for Image processing and Computer vision -A Review

2018 ◽  
Vol 1 (2) ◽  
pp. 17-23
Author(s):  
Takialddin Al Smadi
Keyword(s):  
Image Processing ◽  
Computer Vision ◽  
Augmented Reality ◽  
Video Compression ◽  
Video Processing ◽  
Vision System ◽  
Citrus Fruit ◽  
Modern Technology ◽  
Image And Video Processing ◽  
Depth Video

This survey outlines the use of computer vision in Image and video processing in multidisciplinary applications; either in academia or industry, which are active in this field.The scope of this paper covers the theoretical and practical aspects in image and video processing in addition of computer vision, from essential research to evolution of application.In this paper a various subjects of image processing and computer vision will be demonstrated ,these subjects are spanned from the evolution of mobile augmented reality (MAR) applications, to augmented reality under 3D modeling and real time depth imaging, video processing algorithms will be discussed to get higher depth video compression, beside that in the field of mobile platform an automatic computer vision system for citrus fruit has been implemented ,where the Bayesian classification with Boundary Growing to detect the text in the video scene. Also the paper illustrates the usability of the handed interactive method to the portable projector based on augmented reality.   © 2018 JASET, International Scholars and Researchers Association

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