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Deep Learning for Chest Radiographs

2021

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Deep Learning for Chest Radiographs: Computer-Aided Classification

1, 2021

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A Novel Approach of ECG Signal Compression using MRA Analysis based on WPD

JOURNAL OF SCIENTIFIC RESEARCH, 2022, Vol.66 (3), p.202-211

2022

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Review Paper on Face Recognition Techniques

International Journal of Computer Sciences and Engineering, 2019-05, Vol.7 (5), p.223-229

2019

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Design Spline Adaptive Filter with Fractional Order Adaptive Technique for ECG Signal Enhancement

Augmented human research, 2020-12, Vol.5 (1), Article 4

2020

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HRV Signal Feature Estimation and Classification for Healthcare System Based on Machine Learning

Machine Learning, Image Processing, Network Security and Data Sciences, 2020, Vol.1241, p.437-448

2020

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Performance Comparison of Median and Wiener Filter in Image De-noising

International journal of computer applications, 2010-01, Vol.12 (4), p.27-31

2010

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ECG signal compression using dual-tree sparse decomposition of DWT filters and HRV analysis

Smart Computing, 2021, p.82-89

1, 2021

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Chapter 6 - Hybrid computer-aided classification system design using end-to-end Pre-trained CNN-based deep feature extraction and PCA-SVM classifier for chest radiographs

Deep Learning for Chest Radiographs, 2021, p.157-166

2021

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Chapter 9 - Hybrid computer-aided classification system design using lightweight end-to-end Pre-trained CNN-based deep feature extraction and PCA-SVM classifier for chest radiographs

Deep Learning for Chest Radiographs, 2021, p.197-204

2021

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Chapter 10 - Comparative analysis of computer-aided classification systems designed for chest radiographs: Conclusion and future scope

Deep Learning for Chest Radiographs, 2021, p.205-209

2021

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Chapter 4 - End-to-end pre-trained CNN-based computer-aided classification system design for chest radiographs

Deep Learning for Chest Radiographs, 2021, p.117-140

2021

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Lightweight end-to-end Pre-trained CNN-based computer-aided classification system design for chest radiographs

Deep Learning for Chest Radiographs, 2021

2021

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Chapter 5 - Hybrid computer-aided classification system design using end-to-end CNN-based deep feature extraction and ANFC-LH classifier for chest radiographs

Deep Learning for Chest Radiographs, 2021, p.141-156

2021

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Chapter 1 - Introduction

Deep Learning for Chest Radiographs, 2021, p.1-33

2021

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Chapter 8 - Hybrid computer-aided classification system design using lightweight end-to-end Pre-trained CNN-based deep feature extraction and ANFC-LH classifier for chest radiographs

Deep Learning for Chest Radiographs, 2021, p.185-196

2021

Volltextzugriff (PDF)

End-to-end pre-trained CNN-based computer-aided classification system design for chest radiographs

Deep Learning for Chest Radiographs, 2021

2021

Volltextzugriff (PDF)

Introduction

Deep Learning for Chest Radiographs, 2021

2021

Volltextzugriff (PDF)

Intro

Deep Learning for Chest Radiographs, 2021

2021

Volltextzugriff (PDF)

Hybrid computer-aided classification system design using lightweight end-to-end Pre-trained CNN-based deep feature extract

Deep Learning for Chest Radiographs, 2021

2021

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Deep Learning for Chest Radiographs: Computer-Aided Classification

Deep Learning for Chest Radiographs, 2021

2021

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Chapter 3 - Methodology adopted for designing of computer-aided classification systems for chest radiographs

Deep Learning for Chest Radiographs, 2021, p.59-115

2021

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Review of related work

Deep Learning for Chest Radiographs, 2021

2021

Volltextzugriff (PDF)

Methodology adopted for designing of computer-aided classification systems for chest radiographs

Deep Learning for Chest Radiographs, 2021

2021

Volltextzugriff (PDF)

Hybrid computer-aided classification system design using end-to-end CNN-based deep feature extraction and ANFC-LH classifie

Deep Learning for Chest Radiographs, 2021

2021

Volltextzugriff (PDF)

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Deep Learning for Chest Radiographs

Deep Learning for Chest Radiographs: Computer-Aided Classification

A Novel Approach of ECG Signal Compression using MRA Analysis based on WPD

Review Paper on Face Recognition Techniques

Design Spline Adaptive Filter with Fractional Order Adaptive Technique for ECG Signal Enhancement

HRV Signal Feature Estimation and Classification for Healthcare System Based on Machine Learning

Performance Comparison of Median and Wiener Filter in Image De-noising

ECG signal compression using dual-tree sparse decomposition of DWT filters and HRV analysis

Chapter 6 - Hybrid computer-aided classification system design using end-to-end Pre-trained CNN-based deep feature extraction and PCA-SVM classifier for chest radiographs

Chapter 9 - Hybrid computer-aided classification system design using lightweight end-to-end Pre-trained CNN-based deep feature extraction and PCA-SVM classifier for chest radiographs

Chapter 10 - Comparative analysis of computer-aided classification systems designed for chest radiographs: Conclusion and future scope

Chapter 4 - End-to-end pre-trained CNN-based computer-aided classification system design for chest radiographs

Lightweight end-to-end Pre-trained CNN-based computer-aided classification system design for chest radiographs

Chapter 5 - Hybrid computer-aided classification system design using end-to-end CNN-based deep feature extraction and ANFC-LH classifier for chest radiographs

Chapter 1 - Introduction

Chapter 8 - Hybrid computer-aided classification system design using lightweight end-to-end Pre-trained CNN-based deep feature extraction and ANFC-LH classifier for chest radiographs

End-to-end pre-trained CNN-based computer-aided classification system design for chest radiographs

Introduction

Intro

Hybrid computer-aided classification system design using lightweight end-to-end Pre-trained CNN-based deep feature extract

Deep Learning for Chest Radiographs: Computer-Aided Classification

Chapter 3 - Methodology adopted for designing of computer-aided classification systems for chest radiographs

Review of related work

Methodology adopted for designing of computer-aided classification systems for chest radiographs

Hybrid computer-aided classification system design using end-to-end CNN-based deep feature extraction and ANFC-LH classifie

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