Zobrazeno 1 - 10
of 19
pro vyhledávání: '"Savita Kolhe"'
Autor:
Vennampally Nataraj, Sanjay Gupta, K. H. Singh, Prince Choyal, Raghavendra Nargund, M. Shivakumar, Nisha Agrawal, Giriraj Kumawat, Vangala Rajesh, Rakesh Kumar Verma, Gyanesh K. Satpute, Bairi Srikanth, Savita Kolhe
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-16 (2024)
Abstract Soybean is a rainfed crop grown across a wide range of environments in India. Its grain yield is a complex trait governed by many minor genes and influenced by environmental effects and genotype × environment interactions. In the current in
Externí odkaz:
https://doaj.org/article/dcae410e2b8948c4afa7215c85364d58
Publikováno v:
International Journal of Engineering Trends and Technology. 71:408-420
Publikováno v:
IOP Conference Series: Materials Science and Engineering. 1099:012037
Leaves express the initial symptoms of many diseases in soybean crop. CNN based Computer-Vision (CV) of the leaf-images identifies, enables the diagnosing and controlling the soybean-crop diseases. All three actions need proactive maintenance and Ope
Publikováno v:
Computers and Electronics in Agriculture. 178:105747
Ensemble methods give better performance compared to a single machine learning algorithm. Vote is one of the best ensembles. Vote merges predictions from Simple Logistics and the Naive Bayes algorithms in the present work. The paper presents a new en
Publikováno v:
Computers and Electronics in Agriculture. 124:65-72
New hybrid ensemble algorithm for multiclass classification problems is proposed.It uses machine learning algorithms, feature ranking method and an instance filter.Its aim is to improve the performance results of ensemble-Vote.It is tested on four st
Publikováno v:
IJARCCE. 5:140-143
Publikováno v:
IJIREEICE. 4:42-46
Publikováno v:
Expert Systems with Applications. 38:14592-14601
The paper reports an interface designed for three subsystems-the knowledge acquisition subsystem with dynamic disease knowledge base, intelligent disease diagnosis subsystem with object-oriented intelligent-inference model and intelligent tutor for c
Publikováno v:
Computers and Electronics in Agriculture. 76:16-27
This paper suggests a new approach for providing intelligence in the system for diagnosis of diseases of the oilseed-crops. It reports the development of a web-based intelligent disease diagnosis system (WIDDS). The WIDDS is based on a new fuzzy logi
Autor:
Nataraj, Vennampally1 (AUTHOR), Gupta, Sanjay1 (AUTHOR) sanitaishu@gmail.com, Singh, K. H.1 (AUTHOR), Choyal, Prince1 (AUTHOR), Nargund, Raghavendra1 (AUTHOR), Shivakumar, M.1 (AUTHOR), Agrawal, Nisha1 (AUTHOR), Kumawat, Giriraj1 (AUTHOR), Rajesh, Vangala1 (AUTHOR), Verma, Rakesh Kumar1 (AUTHOR), Satpute, Gyanesh K.1 (AUTHOR), Srikanth, Bairi2 (AUTHOR), Kolhe, Savita1 (AUTHOR)
Publikováno v:
Scientific Reports. 5/21/2024, Vol. 11 Issue 1, p1-16. 16p.