Zobrazeno 1 - 9
of 9
pro vyhledávání: '"Shyamal S. Virnodkar"'
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
Autor:
Sunil Kumar Jha, Virupakshagouda C. Patil, Rekha B.U, Shyamal S. Virnodkar, Sergey A. Bartalev, Dmitry Plotnikov, Evgeniya Elkina, Nilanchal Patel
Publikováno v:
Universal Journal of Agricultural Research. 10:699-721
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::4da1e5a56ab40369b5a021cb54cb6505
https://doi.org/10.13189/ujar.2022.100611
https://doi.org/10.13189/ujar.2022.100611
Publikováno v:
International Journal of Lakes and Rivers. 15:67-81
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::187fd57e12dda27bc512fcab18ab76c8
https://doi.org/10.37622/ijlr/15.1.2022.67-81
https://doi.org/10.37622/ijlr/15.1.2022.67-81
Publikováno v:
Journal of King Saud University - Computer and Information Sciences. 34:3343-3355
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://explore.openaire.eu/search/publication?articleId=doi_________::c7494f6ff9355095b2d183ff8ecf09e7
https://doi.org/10.1016/j.jksuci.2020.09.005
https://doi.org/10.1016/j.jksuci.2020.09.005
Publikováno v:
Traitement du Signal. 38:1131-1139
A single most immense abiotic stress globally affecting the productivity of all the crops is water stress. Hence, timely and accurate detection of the water-stressed crops is a necessary task for high productivity. Agricultural crop production can be
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::10401e31ecfeb7a06f14c4c9a62ebc22
https://doi.org/10.18280/ts.380424
https://doi.org/10.18280/ts.380424
Publikováno v:
Precision Agriculture. 21:1121-1155
The remote sensing (RS) technique is less cost- and labour- intensive than ground-based surveys for diverse applications in agriculture. Machine learning (ML), a branch of artificial intelligence (AI), provides an effective approach to construct a mo
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::fec61bb2abf26ca7ca3961cdc280a89a
https://doi.org/10.1007/s11119-020-09711-9
https://doi.org/10.1007/s11119-020-09711-9
Publikováno v:
Advances in Intelligent Systems and Computing ISBN: 9789811563522
ICACIE (2)
ICACIE (2)
Satellite imagery data collected from various modern and older versions of satellites discover its applications in a variety of domains. One of the domains with great importance is the agriculture domain. Satellite imagery data can be significantly u
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::47faea5a3d795a8bbf5b0288c84ad961
https://doi.org/10.1007/978-981-15-6353-9_29
https://doi.org/10.1007/978-981-15-6353-9_29
Publikováno v:
Advances in Intelligent Systems and Computing ISBN: 9789811563522
ICACIE (2)
ICACIE (2)
Sentinel-2 optical time-series images obtained at high resolution are creditable for cropland mapping which is the key for sustainable agriculture. The presented work was conducted in a heterogeneous region in Sameerwadi with an aim to classify sugar
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::e33af158dc918cc1d16b84bd40e8c4eb
https://doi.org/10.1007/978-981-15-6353-9_15
https://doi.org/10.1007/978-981-15-6353-9_15
Publikováno v:
ICT Analysis and Applications ISBN: 9789811506291
Sugarcane is a major contributing component in the economy of tropical and subtropical countries like India, Brazil and China. Sugarcane agriculture is empowered with the advancements in the remote sensing technology because of its timely, non invasi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::5cf0b0f46928cec579ae01ee0bb633ce
https://doi.org/10.1007/978-981-15-0630-7_55
https://doi.org/10.1007/978-981-15-0630-7_55