Zobrazeno 1 - 9
of 9
pro vyhledávání: '"Chetan Badgujar"'
Publikováno v:
Sensors, Vol 24, Iss 23, p 7858 (2024)
Deep learning applications in agriculture are advancing rapidly, leveraging data-driven learning models to enhance crop yield and nutrition. Tomato (Solanum lycopersicum), a vegetable crop, frequently suffers from pest damage and drought, leading to
Externí odkaz:
https://doaj.org/article/0d35590571f545b3b6181618548088d9
Application of Computational Intelligence Methods in Agricultural Soil–Machine Interaction: A Review
Publikováno v:
Agriculture, Vol 13, Iss 2, p 357 (2023)
Rapid advancements in technology, particularly in soil tools and agricultural machinery, have led to the proliferation of mechanized agriculture. The interaction between such tools/machines and soil is a complex, dynamic process. The modeling of this
Externí odkaz:
https://doaj.org/article/f14cafdd5bc040c3b9ff30f4e230aa03
Publikováno v:
Sensors, Vol 22, Iss 16, p 6203 (2022)
Pest infestation causes significant crop damage during crop production, which reduces the crop yield in terms of quality and quantity. Accurate, precise, and timely information on pest infestation is a crucial aspect of integrated pest management pra
Externí odkaz:
https://doaj.org/article/85919dc9fa82419698f9b77811c2a24b
Publikováno v:
Journal of Field Robotics. 40:919-933
Publikováno v:
2022 IEEE Symposium Series on Computational Intelligence (SSCI).
Soil working tools, implements, and machines are inevitable in mechanized agriculture. The soil-tool/machine interaction is a multivariate, dynamic, and intricate process. The accurate interpretation, description, and modeling of a soil-machine inter
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::438cfb4602087a8da636c3ca1472659b
https://doi.org/10.20944/preprints202210.0391.v1
https://doi.org/10.20944/preprints202210.0391.v1
Publikováno v:
2022 Houston, Texas July 17-20, 2022.
Publikováno v:
Computers and Electronics in Agriculture. 196:106867
Autor:
Chetan Badgujar, Praveen Kumar
Publikováno v:
Lecture Notes in Mechanical Engineering ISBN: 9789811364150
In the present work, flow characteristics of high sulfur crude oil (HSCO) with the addition of low sulfur crude oil (LSCO) were studied. LSCO was mixed in high sulfur crude oil in concentration of 10–15% by volume. The rheological characteristics o
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::81378740225b8bd7adcff12dd1cd6335
https://doi.org/10.1007/978-981-13-6416-7_44
https://doi.org/10.1007/978-981-13-6416-7_44