Zobrazeno 1 - 10
of 29
pro vyhledávání: '"B. R. Mohan"'
Publikováno v:
International Journal on Recent and Innovation Trends in Computing and Communication. 11:178-185
In this research, we aim to determine the water potability using three machine learning classification algorithms: decision tree, gradient boosting and bagging classifier. These algorithms were trained and tested on a dataset of water quality measure
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::667b9248a22d52de96500527cbda10a4
https://doi.org/10.17762/ijritcc.v11i3.6333
https://doi.org/10.17762/ijritcc.v11i3.6333
Publikováno v:
International Journal on Recent and Innovation Trends in Computing and Communication. 11:135-143
Nowadays, Tumour is one of the important reasons of human death worldwide, producing about 9.6 million people in 2018. BC (breast cancer) is the common reason for cancer deaths in females. BC is a type of cancer that can be treated when detected earl
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::6408b687c45268be50ea027c2312f257
https://doi.org/10.17762/ijritcc.v11i3s.6174
https://doi.org/10.17762/ijritcc.v11i3s.6174
Publikováno v:
International Journal on Recent and Innovation Trends in Computing and Communication. 11:43-51
The deployment of self-learning computer algorithms that can automatically enhance their performance via experience is referred to as machine learning in ecommerce and is a crucial trend of the retail digital transformation. Machine learning algorith
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::e0594fe3e2ec47c8a8acb9d9ee92f3e8
https://doi.org/10.17762/ijritcc.v11i1s.5992
https://doi.org/10.17762/ijritcc.v11i1s.5992
Publikováno v:
International journal of health sciences. :1650-1667
Medical imaging is extremely important in the domain of medicine. Image classification is now utilized to distinguish aberrant tissues from healthy tissue in brain imaging. The brain tumor is identified from MRI images by using some classification te
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::12236019ce3f1109636627406533f8cf
https://doi.org/10.53730/ijhs.v6ns5.9153
https://doi.org/10.53730/ijhs.v6ns5.9153
Autor:
Swaroop Hebbale, Ashapurna Marndi, B H Manjunatha Kumar, B R Mohan, Prasad N Achyutha, Piyush Kumar Pareek
Publikováno v:
International journal of health sciences. :7850-7865
Deep Learning has indeed been widely used in many fields/areas of medicinal images classification, and a large number of publications have been published documenting its success. The key for achieving effective diagnosis and therapy is accurate chara
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::070cb5005cdd6609a067327b9088fbd6
https://doi.org/10.53730/ijhs.v6ns1.6791
https://doi.org/10.53730/ijhs.v6ns1.6791
Publikováno v:
Plastics, Rubber and Composites. 52:129-144
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::06f6cc5e4fbfdd07520ebe62fe5b5e39
https://doi.org/10.1080/14658011.2021.2021839
https://doi.org/10.1080/14658011.2021.2021839
Publikováno v:
Materials Research Express, Vol 7, Iss 1, p 015324 (2020)
The present work focused on electromagnetic (EM) absorption performance comparison of different polymer nanocomposite structures. Synthesis and fabrication of polymer nanocomposite composed of graphene, polyurethane (PU), epoxy was done using in situ
Externí odkaz:
https://doaj.org/article/b5bf537766694eb88d86ce04a5fa1d79
Publikováno v:
Plastics, Rubber & Composites; Apr2023, Vol. 52 Issue 3, p129-144, 16p
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Publikováno v:
SSRN Electronic Journal.
Ongoing developments in clinical records have extended patients information out of cutoff points in HealthCare area. Clinical data is exemplified in an advanced type of patient illness data source promptly accessible for Doctor's reference. Bunching
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::87cefac7113805439fb005081802637a
https://doi.org/10.2139/ssrn.3835006
https://doi.org/10.2139/ssrn.3835006