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1
Explaining classifiers by constructing familiar concepts
Explaining classifiers by constructing familiar concepts
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Explaining classifiers by constructing familiar concepts

Machine learning, 2023-11, Vol.112 (11), p.4167-4200 [Peer Reviewed Journal]

The Author(s) 2022 ;ISSN: 0885-6125 ;EISSN: 1573-0565 ;DOI: 10.1007/s10994-022-06157-0

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2
MRI-Based Brain Tumor Classification Using Ensemble of Deep Features and Machine Learning Classifiers
MRI-Based Brain Tumor Classification Using Ensemble of Deep Features and Machine Learning Classifiers
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MRI-Based Brain Tumor Classification Using Ensemble of Deep Features and Machine Learning Classifiers

Sensors (Basel, Switzerland), 2021-03, Vol.21 (6), p.2222 [Peer Reviewed Journal]

2021 by the authors. 2021 ;ISSN: 1424-8220 ;EISSN: 1424-8220 ;DOI: 10.3390/s21062222 ;PMID: 33810176

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3
Galaxy Merger Rates up to z ∼ 3 Using a Bayesian Deep Learning Model: A Major-merger Classifier Using IllustrisTNG Simulation Data
Galaxy Merger Rates up to z ∼ 3 Using a Bayesian Deep Learning Model: A Major-merger Classifier Using IllustrisTNG Simulation Data
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Galaxy Merger Rates up to z ∼ 3 Using a Bayesian Deep Learning Model: A Major-merger Classifier Using IllustrisTNG Simulation Data

The Astrophysical journal, 2020-06, Vol.895 (2), p.115 [Peer Reviewed Journal]

2020. The American Astronomical Society. All rights reserved. ;Copyright IOP Publishing Jun 01, 2020 ;ISSN: 0004-637X ;EISSN: 1538-4357 ;DOI: 10.3847/1538-4357/ab8f9b

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4
Novel deep genetic ensemble of classifiers for arrhythmia detection using ECG signals
Novel deep genetic ensemble of classifiers for arrhythmia detection using ECG signals
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Novel deep genetic ensemble of classifiers for arrhythmia detection using ECG signals

Neural computing & applications, 2020-08, Vol.32 (15), p.11137-11161 [Peer Reviewed Journal]

The Author(s) 2019 ;The Author(s) 2019. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;ISSN: 0941-0643 ;EISSN: 1433-3058 ;DOI: 10.1007/s00521-018-03980-2

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5
Sex‐related patterns in the electroencephalogram and their relevance in machine learning classifiers
Sex‐related patterns in the electroencephalogram and their relevance in machine learning classifiers
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Sex‐related patterns in the electroencephalogram and their relevance in machine learning classifiers

Human brain mapping, 2023-10, Vol.44 (14), p.4848-4858 [Peer Reviewed Journal]

2023 The Authors. published by Wiley Periodicals LLC. ;2023 The Authors. Human Brain Mapping published by Wiley Periodicals LLC. ;2023. This article is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;ISSN: 1065-9471 ;EISSN: 1097-0193 ;DOI: 10.1002/hbm.26417 ;PMID: 37461294

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6
Privacy preserving distributed learning classifiers – Sequential learning with small sets of data
Privacy preserving distributed learning classifiers – Sequential learning with small sets of data
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Privacy preserving distributed learning classifiers – Sequential learning with small sets of data

Computers in biology and medicine, 2021-09, Vol.136, p.104716-104716, Article 104716 [Peer Reviewed Journal]

2021 The Author(s) ;2021. The Author(s) ;ISSN: 0010-4825 ;EISSN: 1879-0534 ;DOI: 10.1016/j.compbiomed.2021.104716

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7
Variational quantum classifiers through the lens of the Hessian
Variational quantum classifiers through the lens of the Hessian
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Variational quantum classifiers through the lens of the Hessian

PloS one, 2022-01, Vol.17 (1), p.e0262346-e0262346 [Peer Reviewed Journal]

COPYRIGHT 2022 Public Library of Science ;2022 Sen et al. This is an open access article distributed under the terms of the Creative Commons Attribution License: http://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;2022 Sen et al 2022 Sen et al ;ISSN: 1932-6203 ;EISSN: 1932-6203 ;DOI: 10.1371/journal.pone.0262346 ;PMID: 35051206

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8
A deep-learning classifier identifies patients with clinical heart failure using whole-slide images of H&E tissue
A deep-learning classifier identifies patients with clinical heart failure using whole-slide images of H&E tissue
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A deep-learning classifier identifies patients with clinical heart failure using whole-slide images of H&E tissue

PloS one, 2018-04, Vol.13 (4), p.e0192726-e0192726 [Peer Reviewed Journal]

COPYRIGHT 2018 Public Library of Science ;COPYRIGHT 2018 Public Library of Science ;2018 Nirschl et al. This is an open access article distributed under the terms of the Creative Commons Attribution License: http://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;2018 Nirschl et al 2018 Nirschl et al ;ISSN: 1932-6203 ;EISSN: 1932-6203 ;DOI: 10.1371/journal.pone.0192726 ;PMID: 29614076

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9
Ensembles of Patch-Based Classifiers for Diagnosis of Alzheimer Diseases
Ensembles of Patch-Based Classifiers for Diagnosis of Alzheimer Diseases
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Ensembles of Patch-Based Classifiers for Diagnosis of Alzheimer Diseases

IEEE access, 2019, Vol.7, p.73373-73383 [Peer Reviewed Journal]

Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 2019 ;ISSN: 2169-3536 ;EISSN: 2169-3536 ;DOI: 10.1109/ACCESS.2019.2920011 ;CODEN: IAECCG

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10
Bagging and Boosting Ensemble Classifiers for Classification of Multispectral, Hyperspectral and PolSAR Data: A Comparative Evaluation
Bagging and Boosting Ensemble Classifiers for Classification of Multispectral, Hyperspectral and PolSAR Data: A Comparative Evaluation
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Bagging and Boosting Ensemble Classifiers for Classification of Multispectral, Hyperspectral and PolSAR Data: A Comparative Evaluation

Remote sensing (Basel, Switzerland), 2021-11, Vol.13 (21), p.4405 [Peer Reviewed Journal]

2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;ISSN: 2072-4292 ;EISSN: 2072-4292 ;DOI: 10.3390/rs13214405

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11
Comparing Deep Neural Networks, Ensemble Classifiers, and Support Vector Machine Algorithms for Object-Based Urban Land Use/Land Cover Classification
Comparing Deep Neural Networks, Ensemble Classifiers, and Support Vector Machine Algorithms for Object-Based Urban Land Use/Land Cover Classification
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Comparing Deep Neural Networks, Ensemble Classifiers, and Support Vector Machine Algorithms for Object-Based Urban Land Use/Land Cover Classification

Remote sensing (Basel, Switzerland), 2019-07, Vol.11 (14), p.1713 [Peer Reviewed Journal]

2019. This work is licensed under https://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;ISSN: 2072-4292 ;EISSN: 2072-4292 ;DOI: 10.3390/rs11141713

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12
A survey of deep network techniques all classifiers can adopt
A survey of deep network techniques all classifiers can adopt
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A survey of deep network techniques all classifiers can adopt

Data mining and knowledge discovery, 2021-01, Vol.35 (1), p.46-87 [Peer Reviewed Journal]

The Author(s), under exclusive licence to Springer Science+Business Media LLC, part of Springer Nature 2020 ;The Author(s), under exclusive licence to Springer Science+Business Media LLC, part of Springer Nature 2020. ;ISSN: 1384-5810 ;EISSN: 1573-756X ;DOI: 10.1007/s10618-020-00722-8 ;PMID: 34584490

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13
Calibrating Deep Learning Classifiers for Patient-Independent Electroencephalogram Seizure Forecasting
Calibrating Deep Learning Classifiers for Patient-Independent Electroencephalogram Seizure Forecasting
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Calibrating Deep Learning Classifiers for Patient-Independent Electroencephalogram Seizure Forecasting

Sensors (Basel, Switzerland), 2024-05, Vol.24 (9), p.2863 [Peer Reviewed Journal]

COPYRIGHT 2024 MDPI AG ;2024 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;ISSN: 1424-8220 ;EISSN: 1424-8220 ;DOI: 10.3390/s24092863 ;PMID: 38732969

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14
An Adaptive Multi-Layer Botnet Detection Technique Using Machine Learning Classifiers
An Adaptive Multi-Layer Botnet Detection Technique Using Machine Learning Classifiers
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An Adaptive Multi-Layer Botnet Detection Technique Using Machine Learning Classifiers

Applied sciences, 2019-06, Vol.9 (11), p.2375 [Peer Reviewed Journal]

2019. This work is licensed under https://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;ISSN: 2076-3417 ;EISSN: 2076-3417 ;DOI: 10.3390/app9112375

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15
Evaluation of Different Bearing Fault Classifiers in Utilizing CNN Feature Extraction Ability
Evaluation of Different Bearing Fault Classifiers in Utilizing CNN Feature Extraction Ability
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Evaluation of Different Bearing Fault Classifiers in Utilizing CNN Feature Extraction Ability

Sensors (Basel, Switzerland), 2022-04, Vol.22 (9), p.3314 [Peer Reviewed Journal]

2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;2022 by the authors. 2022 ;ISSN: 1424-8220 ;EISSN: 1424-8220 ;DOI: 10.3390/s22093314 ;PMID: 35591006

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16
Ear recognition with ensemble classifiers; A deep learning approach
Ear recognition with ensemble classifiers; A deep learning approach
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Ear recognition with ensemble classifiers; A deep learning approach

Multimedia tools and applications, 2022-12, Vol.81 (30), p.43919-43945 [Peer Reviewed Journal]

The Author(s) 2022 ;The Author(s) 2022. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;ISSN: 1380-7501 ;EISSN: 1573-7721 ;DOI: 10.1007/s11042-022-13252-w

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17
Explainability and Transparency of Classifiers for Air-Handling Unit Faults Using Explainable Artificial Intelligence (XAI)
Explainability and Transparency of Classifiers for Air-Handling Unit Faults Using Explainable Artificial Intelligence (XAI)
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Explainability and Transparency of Classifiers for Air-Handling Unit Faults Using Explainable Artificial Intelligence (XAI)

Sensors (Basel, Switzerland), 2022-08, Vol.22 (17), p.6338 [Peer Reviewed Journal]

COPYRIGHT 2022 MDPI AG ;2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;2022 by the authors. 2022 ;ISSN: 1424-8220 ;EISSN: 1424-8220 ;DOI: 10.3390/s22176338 ;PMID: 36080795

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18
Diabetic retinopathy classification based on multipath CNN and machine learning classifiers
Diabetic retinopathy classification based on multipath CNN and machine learning classifiers
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Diabetic retinopathy classification based on multipath CNN and machine learning classifiers

Australasian physical & engineering sciences in medicine, 2021-09, Vol.44 (3), p.639-653 [Peer Reviewed Journal]

Australasian College of Physical Scientists and Engineers in Medicine 2021. ;ISSN: 0158-9938 ;EISSN: 1879-5447 ;DOI: 10.1007/s13246-021-01012-3

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19
Tri-model classifiers for EEG based mental task classification: hybrid optimization assisted framework
Tri-model classifiers for EEG based mental task classification: hybrid optimization assisted framework
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Tri-model classifiers for EEG based mental task classification: hybrid optimization assisted framework

BMC bioinformatics, 2023-10, Vol.24 (1), p.1-406, Article 406 [Peer Reviewed Journal]

COPYRIGHT 2023 BioMed Central Ltd. ;2023. This work is licensed under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;The Author(s) 2023 ;ISSN: 1471-2105 ;EISSN: 1471-2105 ;DOI: 10.1186/s12859-023-05544-1

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20
Multiple Classifiers Based Semi-Supervised Polarimetric SAR Image Classification Method
Multiple Classifiers Based Semi-Supervised Polarimetric SAR Image Classification Method
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Multiple Classifiers Based Semi-Supervised Polarimetric SAR Image Classification Method

Sensors (Basel, Switzerland), 2021-04, Vol.21 (9), p.3006 [Peer Reviewed Journal]

2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;2021 by the authors. 2021 ;ISSN: 1424-8220 ;EISSN: 1424-8220 ;DOI: 10.3390/s21093006 ;PMID: 33922957

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