ARCHIVES
Original Article
Precision Grape Plantation Management: Harnessing CS-ML Approaches
Pandey Rajnish1
Kumar Chandan2
Singh Rajesh Kumar3
12 Department of Computer Science Engineering, Doon College of Engineering Technology, UP, India. 3Assistant Professor, Department of Computer Science Engineering, Doon College of Engineering Technology, UP, India.
Published Online: September-October 2024
Pages: 28-31
Cite this article
No DOIReferences
1. Arturo Aquino, Maria P. Diago, Borja Millan, Javier Tard Aguila, “A new methodology for estimating the grapevine berry number per
cluster using image analysis”, Biosystems Engineering, Vol. 156, pp. 80-95, 2017.
2. Tardaguila, J., Diago, M.P., Millán, B., Blasco, J., Cubero, S. García-Navarrete, O.L., and Aleixos, N., “Automatic estimation of the size
and weight of grapevine berries by image analysis”, CIGR- AgEng., 2012.
3. G. M. Dunn, S. R. Martin, "Yield prediction from digitial image analysis: a technique with potential for vineyard assessments prior to
harvest.", Australian Journal of Grape and Wine Research, 10, pp.196-198, 2004.
4. Chamelat, R., Rosso, E., Choksuriwong, A., Rosenberger, C., Laurent, H., and Bro, P., “Grape Detection by Image Processing”,
Proceedings of IEEE 32nd Annual Conference on Industrial Electronics (IECON 2006), Paris, France. pp. 3697–3702, 2006.
5. Rabatel, G., &Guizard, C., “Grape berry calibration by computer vision using elliptical model fitting”, 6th European Conference on
Precision Agriculture (ECPA 2007), Skiathos, Greece. pp. 581-587, 2007
cluster using image analysis”, Biosystems Engineering, Vol. 156, pp. 80-95, 2017.
2. Tardaguila, J., Diago, M.P., Millán, B., Blasco, J., Cubero, S. García-Navarrete, O.L., and Aleixos, N., “Automatic estimation of the size
and weight of grapevine berries by image analysis”, CIGR- AgEng., 2012.
3. G. M. Dunn, S. R. Martin, "Yield prediction from digitial image analysis: a technique with potential for vineyard assessments prior to
harvest.", Australian Journal of Grape and Wine Research, 10, pp.196-198, 2004.
4. Chamelat, R., Rosso, E., Choksuriwong, A., Rosenberger, C., Laurent, H., and Bro, P., “Grape Detection by Image Processing”,
Proceedings of IEEE 32nd Annual Conference on Industrial Electronics (IECON 2006), Paris, France. pp. 3697–3702, 2006.
5. Rabatel, G., &Guizard, C., “Grape berry calibration by computer vision using elliptical model fitting”, 6th European Conference on
Precision Agriculture (ECPA 2007), Skiathos, Greece. pp. 581-587, 2007
Related Articles
2024
Matrix Representation of Graph Theory in Hydrocarbons
2024
A Review of Development of Chemical Sensors
2024
Towards Detection and Attribution of Cyber Attacks in IoT Enabled Cyber-Physical Systems
2024
Implementation of Waste Management System
2024
To Study the Role of Forest –Based Industries in Promoting Trade
2024
