Author: Rahul Kumar; Ridhi Arora; Vipul Bansal; Vinodh J Sahayasheela; Himanshu Buckchash; Javed Imran; Narayanan Narayanan; Ganesh N Pandian; Balasubramanian Raman
Title: Accurate Prediction of COVID-19 using Chest X-Ray Images through Deep Feature Learning model with SMOTE and Machine Learning Classifiers Document date: 2020_4_17
ID: 59ghorzf_18
Snippet: The proposed framework for accurate prediction of COVID-19 using the chest X-ray images through deep feature learning model with SMOTE and machine learning classifiers consisted of the ResNet152 architecture for the training with later using the concerned features to classify the chest X-ray images using machine learning classifiers. The proposed framework is depicted in Figure 5 . A detailed description of the architecture is explained below......
Document: The proposed framework for accurate prediction of COVID-19 using the chest X-ray images through deep feature learning model with SMOTE and machine learning classifiers consisted of the ResNet152 architecture for the training with later using the concerned features to classify the chest X-ray images using machine learning classifiers. The proposed framework is depicted in Figure 5 . A detailed description of the architecture is explained below.
Search related documents:
Co phrase search for related documents- accurate prediction and machine learning: 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71
- accurate prediction and machine learning classifier: 1, 2
- accurate prediction and propose framework: 1, 2, 3, 4
- architecture detailed description and detailed description: 1, 2, 3
- concerned feature and feature learning: 1, 2
- detailed description and machine learning: 1, 2, 3, 4
- feature learning and machine learning: 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73
- feature learning and machine learning classifier: 1, 2, 3, 4, 5, 6, 7
- feature learning and propose framework: 1, 2, 3, 4, 5, 6
- feature learning model and machine learning: 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12
- feature learning model and machine learning classifier: 1
- machine learning and propose framework: 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60
- machine learning classifier and propose framework: 1, 2, 3, 4
Co phrase search for related documents, hyperlinks ordered by date