Zobrazeno 1 - 10
of 48
pro vyhledávání: '"B Sathya Bama"'
Publikováno v:
Data in Brief, Vol 49, Iss , Pp 109321- (2023)
This dataset provides three classes of hyperspectral images: pure, insecticide-immersed, and fungicide-immersed apples with different concentrations of fertilizers. The hyperspectral images were calibrated under white and dark correction and enhanced
Externí odkaz:
https://doaj.org/article/826849d4b7034d8f99fec5d5a6308a82
Publikováno v:
Engineering Science and Technology, an International Journal, Vol 22, Iss 3, Pp 715-726 (2019)
In Remote Sensing, fusion of Panchromatic (PAN) image and Multispectral (MS) image is an important technique. This paper incorporates a multiresolution image fusion algorithm based on the proposed Spatial Frequency DWT (SFDWT – Spatial Frequency Di
Externí odkaz:
https://doaj.org/article/0c3109124e9c4c45b8455b8b06b39836
Publikováno v:
Journal of Intelligent & Fuzzy Systems. 42:5097-5112
Plant species identification is essential for healthy survival as well as the preservation and protection of biodiversity. Manual identification is time-consuming, hence to address this issue deep learning algorithms for automated plant species ident
Autor:
B, Sathya Bama, Y, Bevish Jinila
Publikováno v:
Health Systems; January 2024, Vol. 13 Issue: 1 p62-72, 11p
Autor:
B. Sathya Bama, Y. Bevish Jinila
Publikováno v:
International Journal of Modeling, Simulation, and Scientific Computing.
Parkinson’s disease (PD) is a neurological disease that produces uncontrollable movements and a variety of other symptoms. It can be difficult to make an accurate PD diagnosis since the signs and symptoms, especially early on, might be mistaken for
Autor:
B., Sathya Bama, Y., Bevish Jinila
Publikováno v:
Intelligent Automation & Soft Computing; 2023, Vol. 36 Issue 2, p2085-2097, 13p
Autor:
Boaz Arad, Radu Timofte, Rony Yahel, Nimrod Morag, Amir Bernat, Yuanhao Cai, Jing Lin, Zudi Lin, Haoqian Wang, Yulun Zhang, Hanspeter Pfister, Luc Van Gool, Shuai Liu, Yongqiang Li, Chaoyu Feng, Lei Lei, Jiaojiao Li, Songcheng Du, Chaoxiong Wu, Yihong Leng, Rui Song, Mingwei Zhang, Chongxing Song, Shuyi Zhao, Zhiqiang Lang, Wei Wei, Lei Zhang, Renwei Dian, Tianci Shan, Anjing Guo, Chengguo Feng, Jinyang Liu, Mirko Agarla, Simone Bianco, Marco Buzzelli, Luigi Celona, Raimondo Schettini, Jiang He, Yi Xiao, Jiajun Xiao, Qiangqiang Yuan, Jie Li, Liangpei Zhang, Taesung Kwon, Dohoon Ryu, Hyokyoung Bae, Hao-Hsiang Yang, Hua-En Chang, Zhi-Kai Huang, Wei-Ting Chen, Sy-Yen Kuo, Junyu Chen, Haiwei Li, Song Liu, Sabarinathan Sabarinathan, K Uma, B Sathya Bama, S. Mohamed Mansoor Roomi
This paper reviews the third biennial challenge on spectral reconstruction from RGB images, i.e., the recovery of whole-scene hyperspectral (HS) information from a 3-channel RGB image. This challenge presents the "ARAD_1K"data set: a new, larger-than
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b14c6f9646b01a471ce946e43634fa64
http://hdl.handle.net/11583/2971543
http://hdl.handle.net/11583/2971543
Autor:
D. Synthiya Vinothini, B. Sathya Bama
Publikováno v:
IEEE Sensors Journal. 19:12279-12285
Pan-sharpening is a multi-sensor fusion task that aims to enhance the spatial resolution of spectral data using panchromatic data of the same scene. This work proposes a deep Residual Dense Model (RDM) for Pan-Sharpening (PS) of satellite data which
Publikováno v:
Proceedings of the Twelfth Indian Conference on Computer Vision, Graphics and Image Processing.
Publikováno v:
Engineering Science and Technology, an International Journal, Vol 22, Iss 3, Pp 715-726 (2019)
In Remote Sensing, fusion of Panchromatic (PAN) image and Multispectral (MS) image is an important technique. This paper incorporates a multiresolution image fusion algorithm based on the proposed Spatial Frequency DWT (SFDWT – Spatial Frequency Di