Multiclass COVID-19 detection by utilizing ESN-MDFS: Extreme Smart Network using mean dropout feature selection technique.

Multiclass COVID-19 detection by utilizing ESN-MDFS: Extreme Smart Network using mean dropout feature selection technique.

<p>Multiclass COVID-19 detection by utilizing ESN-MDFS: Extreme Smart Network using mean dropout feature selection technique.</p>

محفوظ في:

التفاصيل البيبلوغرافية
المؤلف الرئيسي:	Saghir Ahmed (4416544) (author)
مؤلفون آخرون:	Basit Raza (20175794) (author), Lal Hussain (14100502) (author), Touseef Sadiq (20175797) (author), Ashit Kumar Dutta (11547381) (author)
منشور في:	2024
الموضوعات:	Cancer Space Science Biological Sciences not elsewhere classified Information Systems not elsewhere classified publicly available sources promising significant advancements portable chest x novel approach called large dataset containing extreme smart network 000 cxr images model &# 8217 images encompass covid enhancing multiclass covid enhancing covid prediction mdfs model achieved 16 model 19 prediction trained vgg superior ability study explores study aimed research proposes optimize performance normal conditions normal cases meticulously addressed mdfs ). hyperparameter tuning fold cross findings demonstrate enhance multi data imbalance cxrs ). bacterial pneumonia
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الوصف
الملخص:	<p>Multiclass COVID-19 detection by utilizing ESN-MDFS: Extreme Smart Network using mean dropout feature selection technique.</p>

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