Zobrazeno 1 - 10 of 34 pro vyhledávání: '"Vimal K. Shrivastava"'
1
Akademický článek
Transfer Learning-Based Framework for Classification of Pest in Tomato Plants
Autor: Gayatri Pattnaik, Vimal K. Shrivastava, K. Parvathi
Publikováno v: Applied Artificial Intelligence, Vol 34, Iss 13, Pp 981-993 (2020)
Pest in the plant is a major challenge in the agriculture sector. Hence, early and accurate detection and classification of pests could help in precautionary measures while substantially reducing economic losses. Recent developments in deep convoluti
Externí odkaz: https://doaj.org/article/6feb45049e994f2eb021672af9e9eb21
Zobrazit plný text záznamu
2
Diagnosis of COVID-19 based on chest X-ray images using pre-trained deep convolutional neural networks
Autor: Vimal K. Shrivastava, Monoj K. Pradhan
Publikováno v: Intelligent Decision Technologies. 16:169-180
The novel coronavirus (COVID-19) that emerged and transmitted from China (Wuhan City) had a staggering effect on public health and the world economy. The early diagnosis of COVID-19 has become more important for its treatment and for controlling its
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::9f62dd2ff947e68e32c7a509870c60fa
https://doi.org/10.3233/idt-210002
Zobrazit plný text záznamu
4
Tomato pest classification using deep convolutional neural network with transfer learning, fine tuning and scratch learning
Autor: K. Parvathi, Gayatri Pattnaik, Vimal K. Shrivastava
Publikováno v: Intelligent Decision Technologies. 15:433-442
Pests are major threat to economic growth of a country. Application of pesticide is the easiest way to control the pest infection. However, excessive utilization of pesticide is hazardous to environment. The recent advances in deep learning have pave
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::2c5f4ad37199d389dab15e6f1ace87a6
https://doi.org/10.3233/idt-200192
Zobrazit plný text záznamu
5
Rice plant disease classification using color features: a machine learning paradigm
Autor: Monoj K. Pradhan, Vimal K. Shrivastava
Publikováno v: Journal of Plant Pathology. 103:17-26
In traditional practices, detection of rice plant diseases by experts is a subjective matter whereas by testing in the laboratory is time-consuming. As a consequence, it causes reduction on agricultural production and economic loss to farmers. To ove
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::bff06ac07f60f521a224aa286665caee
https://doi.org/10.1007/s42161-020-00683-3
Zobrazit plný text záznamu
6
Transfer Learning-Based Framework for Classification of Pest in Tomato Plants
Autor: K. Parvathi, Vimal K. Shrivastava, Gayatri Pattnaik
Publikováno v: Applied Artificial Intelligence. 34:981-993
Pest in the plant is a major challenge in the agriculture sector. Hence, early and accurate detection and classification of pests could help in precautionary measures while substantially reducing e...
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::ef1931d879c3d035e447f73fa5dcf1f3
https://doi.org/10.1080/08839514.2020.1792034
Zobrazit plný text záznamu
7
Effect of pooling strategy on convolutional neural network for classification of hyperspectral remote sensing images
Autor: Vimal K. Shrivastava, Somenath Bera
Publikováno v: IET Image Processing. 14:480-486
The deep convolutional neural network (CNN) has recently attracted the researchers for classification of hyperspectral remote sensing images. The CNN mainly consists of convolution layer, pooling layer and fully connected layer. The pooling is a regu
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::48814cee41f5155006e7e89e01c778c4
https://doi.org/10.1049/iet-ipr.2019.0561
Zobrazit plný text záznamu

Vyhledávací nástroje:

Upřesnit hledání

Omezení vyhledávání
Plný text Recenzováno Digitální knihovna AV ČR
Zdroje