Zobrazeno 1 - 10
of 12
pro vyhledávání: '"Mahantesh. C. Elemmi"'
Autor:
Naveen N. Malvade, Rajesh Yakkundimath, Girish Saunshi, Mahantesh C. Elemmi, Parashuram Baraki
Publikováno v:
Artificial Intelligence in Agriculture, Vol 6, Iss , Pp 167-175 (2022)
The agriculture sector is no exception to the widespread usage of deep learning tools and techniques. In this paper, an automated detection method on the basis of pre-trained Convolutional Neural Network (CNN) models is proposed to identify and class
Externí odkaz:
https://doaj.org/article/2f32afc45f86476e91d6bca4f6ea2f8a
Publikováno v:
Journal of Alternative and Renewable Energy Sources. 9:6-11
Today, technology-driven electricity is one of the significant things for day-to-day activities. It is oblivious that renewable sources of energy are depleting at a fast rate. Hence, it is time for us to move the focus from conventional to non-conven
Publikováno v:
Journal of Computer Science Engineering and Software Testing. 8:50-64
The rate of growth of technology and the interactions of people made from far distance is at its maximum peak in the entire timeline of human history. These times therefore require an individual with accurate and legitimate updated knowledge of the i
Autor:
Sourabh G Patil, Veer Jadimath, Mahantesh C. Elemmi, Pritam Dhumale, Shreyas Deshpande, Naveen N. M.
Publikováno v:
Journal of Computer Science Engineering and Software Testing. 8:35-44
Most of the houses in a city or town get their water supply from their City Corporation or water board. Majority of the areas in a city have a water supply schedule planned. The people living in such areas manage their water usage according to the sc
Publikováno v:
International Journal of Intelligent Systems. 37:2293-2318
Publikováno v:
The Journal of The Textile Institute. 113:1072-1082
The present work gives a comparative analysis of two different classifiers, namely, Support Vector Machine (SVM) and Artificial Neural Network (ANN) to classify defective and non-defective fabric i...
Publikováno v:
International Journal of Image, Graphics and Signal Processing. 11:29-38
Publikováno v:
International Journal of Image, Graphics and Signal Processing. 11:54-61
Publikováno v:
International Journal of Computational Vision and Robotics. 1:1
The presented work gives a methodology to classify fabric images as plain, patterned and unpatterned. Discrete Wavelet Transform is applied and wavelet features are extracted. Feed Backward Selection Technique is used in the feature selection phase.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4a489a53bad355ac4e968fbea5219779