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A classification framework for prediction of breast density using an ensemble of neural network classifiers

Biocybernetics and biomedical engineering, 2017, Vol.37 (1), p.217-228

2017

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Honey Bee Based Improvised BAT Algorithm for Cloud Task Scheduling

International Journal of Computer Networks and Applications, 2023-08, Vol.10 (4), p.494

2023

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Computer Aided Diagnostic System for Detection of Leukemia Using Microscopic Images

Procedia computer science, 2015, Vol.70, p.748-756

2015

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Deep Learning for Chest Radiographs: Computer-Aided Classification

1, 2021

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An efficient node placement scheme to mitigate routing attacks in Internet of Battlefield Things

Computers & electrical engineering, 2022-01, Vol.97, p.107623, Article 107623

2022

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Deep Learning for Chest Radiographs

2021

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Medical image denoising using adaptive fusion of curvelet transform and total variation

Computers & electrical engineering, 2013-07, Vol.39 (5), p.1451-1460

2013

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Glider assisted schemes to deploy sensor nodes in Wireless Sensor Networks

Robotics and autonomous systems, 2018-02, Vol.100, p.1-13

2018

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Deployment schemes in wireless sensor network to achieve blanket coverage in large-scale open area: A review

Egyptian informatics journal, 2016-03, Vol.17 (1), p.45-56

2016

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665P Impact of enzalutamide on patient-reported fatigue in hormone-sensitive prostate cancer (HSPC) or castration-resistant prostate cancer (CRPC)

Annals of oncology, 2020-09, Vol.31, p.S536-S537

2020

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An integrated method for hemorrhage segmentation from brain CT Imaging

Computers & electrical engineering, 2013-07, Vol.39 (5), p.1527-1536

2013

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Wavelet Packet Texture Descriptors Based Four-class BIRADS Breast Tissue Density Classification

Procedia computer science, 2015, Vol.70, p.76-84

2015

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Bioinspired Immune System for Intrusions Detection System in Self Configurable Networks

International journal of advanced computer science & applications, 2019, Vol.10 (10)

2019

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Analysis of effect of cycle spinning on wavelet- and curvelet-based denoising methods on brain CT images

Journal of the Chinese Institute of Engineers, 2014-10, Vol.37 (7), p.939-945

2014

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Depl

Egyptian informatics journal, 2016-03, Vol.17 (1), p.45-56

2016

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MAC Protocols in Wireless Body Area Networks: A Review

International journal of computer applications, 2016-04, Vol.140 (9), p.38-43

2016

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Genetic Analysis in Pearl Millet [Pennisetum glaucum (L) R. Br.]

International journal of current microbiology and applied sciences, 2017-11, Vol.6 (11), p.900-907

2017

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Genetic study for seed yield and seed quality traits in indian mustard [Brassica juncea L. Czern&coss.]

Electronic journal of plant breeding, 2015-09, Vol.6 (3), p.672-679

2015

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Research Methodology in Image Processing

2018 Second International Conference on Intelligent Computing and Control Systems (ICICCS), 2018, p.383-387

2018

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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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Automated brain hemorrhage segmentation using a deep neural network

Smart Computing, 2021, p.180-189

1, 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 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

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A classification framework for prediction of breast density using an ensemble of neural network classifiers

Honey Bee Based Improvised BAT Algorithm for Cloud Task Scheduling

Computer Aided Diagnostic System for Detection of Leukemia Using Microscopic Images

Deep Learning for Chest Radiographs: Computer-Aided Classification

An efficient node placement scheme to mitigate routing attacks in Internet of Battlefield Things

Deep Learning for Chest Radiographs

Medical image denoising using adaptive fusion of curvelet transform and total variation

Glider assisted schemes to deploy sensor nodes in Wireless Sensor Networks

Deployment schemes in wireless sensor network to achieve blanket coverage in large-scale open area: A review

665P Impact of enzalutamide on patient-reported fatigue in hormone-sensitive prostate cancer (HSPC) or castration-resistant prostate cancer (CRPC)

An integrated method for hemorrhage segmentation from brain CT Imaging

Wavelet Packet Texture Descriptors Based Four-class BIRADS Breast Tissue Density Classification

Bioinspired Immune System for Intrusions Detection System in Self Configurable Networks

Analysis of effect of cycle spinning on wavelet- and curvelet-based denoising methods on brain CT images

Depl

MAC Protocols in Wireless Body Area Networks: A Review

Genetic Analysis in Pearl Millet [Pennisetum glaucum (L) R. Br.]

Genetic study for seed yield and seed quality traits in indian mustard [Brassica juncea L. Czern&coss.]

Research Methodology in Image Processing

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

Automated brain hemorrhage segmentation using a deep neural network

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 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

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