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Environmental and Geographical (EG) Image Classification Using FLIM and CNN Algorithms
Intelligent machines have grown in importance in recent years in object recognition in terms of their ability to envision, comprehend, and reach decisions. There are a lot of complicated algorithms that accomplish AI utilities. In addition to their use in the medical industry, these methods of objec...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9402320/ https://www.ncbi.nlm.nih.gov/pubmed/36072629 http://dx.doi.org/10.1155/2022/4989248 |
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author | Ajay, P. Nagaraj, B. Huang, Ruihang Pradeep Raj, M. S. Ananthi, P. |
author_facet | Ajay, P. Nagaraj, B. Huang, Ruihang Pradeep Raj, M. S. Ananthi, P. |
author_sort | Ajay, P. |
collection | PubMed |
description | Intelligent machines have grown in importance in recent years in object recognition in terms of their ability to envision, comprehend, and reach decisions. There are a lot of complicated algorithms that accomplish AI utilities. In addition to their use in the medical industry, these methods of object recognition have a wide range of other fields, most notably industries, in which they can be applied. In contrast to the proposed calculation, the proposed calculation is less complex and more accurate under certain SNR conditions. In the deep nervous tissue fine-tuning discriminator, phantom highlights and binding highlights are separated as sources; modified direct components are used as neuronal activation abilities; and cross entropy is used as unfortunate abilities. Optimized recognition of profound nervous tissue builds profound and periodic nervous tissue for regulatory confirmation of the corresponding signal. |
format | Online Article Text |
id | pubmed-9402320 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Hindawi |
record_format | MEDLINE/PubMed |
spelling | pubmed-94023202022-09-06 Environmental and Geographical (EG) Image Classification Using FLIM and CNN Algorithms Ajay, P. Nagaraj, B. Huang, Ruihang Pradeep Raj, M. S. Ananthi, P. Contrast Media Mol Imaging Research Article Intelligent machines have grown in importance in recent years in object recognition in terms of their ability to envision, comprehend, and reach decisions. There are a lot of complicated algorithms that accomplish AI utilities. In addition to their use in the medical industry, these methods of object recognition have a wide range of other fields, most notably industries, in which they can be applied. In contrast to the proposed calculation, the proposed calculation is less complex and more accurate under certain SNR conditions. In the deep nervous tissue fine-tuning discriminator, phantom highlights and binding highlights are separated as sources; modified direct components are used as neuronal activation abilities; and cross entropy is used as unfortunate abilities. Optimized recognition of profound nervous tissue builds profound and periodic nervous tissue for regulatory confirmation of the corresponding signal. Hindawi 2022-08-17 /pmc/articles/PMC9402320/ /pubmed/36072629 http://dx.doi.org/10.1155/2022/4989248 Text en Copyright © 2022 P. Ajay et al. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Article Ajay, P. Nagaraj, B. Huang, Ruihang Pradeep Raj, M. S. Ananthi, P. Environmental and Geographical (EG) Image Classification Using FLIM and CNN Algorithms |
title | Environmental and Geographical (EG) Image Classification Using FLIM and CNN Algorithms |
title_full | Environmental and Geographical (EG) Image Classification Using FLIM and CNN Algorithms |
title_fullStr | Environmental and Geographical (EG) Image Classification Using FLIM and CNN Algorithms |
title_full_unstemmed | Environmental and Geographical (EG) Image Classification Using FLIM and CNN Algorithms |
title_short | Environmental and Geographical (EG) Image Classification Using FLIM and CNN Algorithms |
title_sort | environmental and geographical (eg) image classification using flim and cnn algorithms |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9402320/ https://www.ncbi.nlm.nih.gov/pubmed/36072629 http://dx.doi.org/10.1155/2022/4989248 |
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