Zobrazeno 1 - 10 of 41 pro vyhledávání: '"SUNIL KUMAR JHA"'
1
Akademický článek
CaneSat dataset to leverage convolutional neural networks for sugarcane classification from Sentinel-2
Autor: Shyamal S. Virnodkar, Vinod K. Pachghare, V.C. Patil, Sunil Kumar Jha
Publikováno v: Journal of King Saud University: Computer and Information Sciences, Vol 34, Iss 6, Pp 3343-3355 (2022)
The ubiquitous deep learning (DL) in remote sensing (RS) motivates the most challenging problem of crop classification. To perpetrate such an exigent task, an attempt is made to prepare a novel dataset, the CaneSat dataset, in two formats: RGB color
Externí odkaz: https://doaj.org/article/f38cb355a40745839e755bd57f706f83
Zobrazit plný text záznamu
2
Akademický článek
Response surface analysis and process optimization of twin screw extrusion of apple pomace blended snacks
Autor: SHAHZAD FAISAL, INDRA MANI, RAM KISHOR GUPTA, P K SAHOO, SUNIL KUMAR JHA, BALJIT SINGH, SUSHEEL K SARKAR, TAPAN K KHURA
Publikováno v: The Indian Journal of Agricultural Sciences, Vol 87, Iss 11 (2017)
Optimization of the extrusion process for apple pomace blended snacks was done using RSM. A blend of apple pomace, maize and soy flour was extruded at five levels of moisture content (12.6–19.4%), barrel temperature (116–184oC) and scre
Externí odkaz: https://doaj.org/article/de8a2037dee0434f8dd7f96336240393
Zobrazit plný text záznamu
3
Akademický článek
Olfaction-Inspired Sensing Using a Sensor System with Molecular Recognition and Optimal Classification Ability for Comprehensive Detection of Gases
Autor: Masahiro Imahashi, Masashi Watanabe, Sunil Kumar Jha, Kenshi Hayashi
Publikováno v: Sensors, Vol 14, Iss 3, Pp 5221-5238 (2014)
In this study, we examined the comprehensive detection of numerous volatile molecules based on the olfactory information constructed by using olfaction-inspired sensor technology. The sensor system can simultaneously detect multiple odors by the sepa
Externí odkaz: https://doaj.org/article/7691ddc4826c4e89be11acb635c913f4
Zobrazit plný text záznamu

Vyhledávací nástroje:

Upřesnit hledání

Omezení vyhledávání
Plný text Recenzováno Digitální knihovna AV ČR
Zdroje