Andrew P. Bradley

According to our database, Andrew P. Bradley authored at least 95 papers between 1996 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Localisation of Racial Information in Chest X-Ray for Deep Learning Diagnosis.

Olivier Salvado, Salamata Konate, Rodrigo Santa Cruz, Andrew P. Bradley, Judy Wawira Gichoya, Laleh Seyyed-Kalantari, Brandon J. Price, Clinton Fookes, Léo Lebrat

Proceedings of the IEEE International Symposium on Biomedical Imaging, 2024

2023

Designing Interaction with AI for Human Learning: Towards Human-Machine Teaming in Radiology Training.

Margot Brereton, Aloha May Hufana Ambe, David R. Lovell, Laurianne Sitbon, Tara Capel, Alessandro Soro, Yue Xu, Catarina Moreira, Benoît Favre, Andrew P. Bradley

Proceedings of the 35th Australian Computer-Human Interaction Conference, 2023

When to Use Augmentation - Variability Insufficient for Cortical Thickness Estimation Improvement.

Filip Rusak, Rodrigo Santa Cruz, Hilda Chourak, Elliot Smith, Jurgen Fripp, Clinton Fookes, Pierrick Bourgeat, Andrew P. Bradley

Proceedings of the 20th IEEE International Symposium on Biomedical Imaging, 2023

Never mind the metrics - what about the uncertainty? Visualising binary confusion matrix metric distributions to put performance in perspective.

David R. Lovell, Dimity Miller, Jaiden Capra, Andrew P. Bradley

Proceedings of the International Conference on Machine Learning, 2023

Bias Identification with RankPix Saliency.

Salamata Konate, Léo Lebrat, Rodrigo Santa Cruz, Clinton Fookes, Andrew P. Bradley, Olivier Salvado

Proceedings of the IEEE International Conference on Acoustics, 2023

2022

Quantifiable brain atrophy synthesis for benchmarking of cortical thickness estimation methods.

Filip Rusak, Rodrigo Santa Cruz, Léo Lebrat, Ondrej Hlinka, Jurgen Fripp, Elliot Smith, Clinton Fookes, Andrew P. Bradley, Pierrick Bourgeat

Medical Image Anal., 2022

Never mind the metrics - what about the uncertainty? Visualising confusion matrix metric distributions.

David R. Lovell, Dimity Miller, Jaiden Capra, Andrew P. Bradley

CoRR, 2022

Lesser of Two Evils Improves Learning in the Context of Cortical Thickness Estimation Models - Choose Wisely.

Filip Rusak, Rodrigo Santa Cruz, Elliot Smith, Jurgen Fripp, Clinton Fookes, Pierrick Bourgeat, Andrew P. Bradley

Proceedings of the Data Augmentation, Labelling, and Imperfections, 2022

2021

Detail Matters: High-Frequency Content for Realistic Synthetic MRI Generation.

Filip Rusak, Rodrigo Santa Cruz, Elliot Smith, Jurgen Fripp, Clinton Fookes, Pierrick Bourgeat, Andrew P. Bradley

Proceedings of the Simulation and Synthesis in Medical Imaging, 2021

Smocam: Smooth Conditional Attention Mask For 3d-Regression Models.

Salamata Konate, Léo Lebrat, Rodrigo Santa Cruz, Pierrick Bourgeat, Vincent Doré, Jurgen Fripp, Andrew P. Bradley, Clinton Fookes, Olivier Salvado

Proceedings of the 18th IEEE International Symposium on Biomedical Imaging, 2021

A Comparison of Saliency Methods for Deep Learning Explainability.

Salamata Konate, Léo Lebrat, Rodrigo Santa Cruz, Elliot Smith, Andrew P. Bradley, Clinton Fookes, Olivier Salvado

Proceedings of the 2021 Digital Image Computing: Techniques and Applications, 2021

Taking the Confusion Out of Multinomial Confusion Matrices and Imbalanced Classes.

David Lovell, Bridget McCarron, Brendan Langfield, Khoa Tran, Andrew P. Bradley

Proceedings of the Data Mining, 2021

2020

Automatic lesion detection, segmentation and characterization via 3D multiscale morphological sifting in breast MRI.

Hang Min, Darryl McClymont, Shekhar S. Chandra, Stuart Crozier, Andrew P. Bradley

CoRR, 2020

Special issue: 4th MICCAI workshop on deep learning in medical image analysis.

Gustavo Carneiro, João Manuel R. S. Tavares, Andrew P. Bradley, João Paulo Papa, Vasileios Belagiannis, Jacinto C. Nascimento, Zhi Lu

Comput. methods Biomech. Biomed. Eng. Imaging Vis., 2020

3D Brain MRI GAN-Based Synthesis Conditioned on Partial Volume Maps.

Filip Rusak, Rodrigo Santa Cruz, Pierrick Bourgeat, Clinton Fookes, Jurgen Fripp, Andrew P. Bradley, Olivier Salvado

Proceedings of the Simulation and Synthesis in Medical Imaging, 2020

Fully Automatic Computer-aided Mass Detection and Segmentation via Pseudo-color Mammograms and Mask R-CNN.

Hang Min, Devin Wilson, Yinhuang Huang, Siyu Liu, Stuart Crozier, Andrew P. Bradley, Shekhar S. Chandra

Proceedings of the 17th IEEE International Symposium on Biomedical Imaging, 2020

2019

Pre and post-hoc diagnosis and interpretation of malignancy from breast DCE-MRI.

Gabriel Maicas, Andrew P. Bradley, Jacinto C. Nascimento, Ian Reid, Gustavo Carneiro

Medical Image Anal., 2019

Fully automatic computer-aided mass detection and segmentation via pseudo-color mammograms and Mask R-CNN.

Hang Min, Devin Wilson, Yinhuang Huang, Samuel Kelly, Stuart Crozier, Andrew P. Bradley, Shekhar S. Chandra

CoRR, 2019

Editorial.

Gustavo Carneiro, João Manuel R. S. Tavares, Andrew P. Bradley, João Paulo Papa, Jacinto C. Nascimento, Jaime S. Cardoso, Zhi Lu, Vasileios Belagiannis

Comput. methods Biomech. Biomed. Eng. Imaging Vis., 2019

Model Agnostic Saliency For Weakly Supervised Lesion Detection From Breast DCE-MRI.

Gabriel Maicas, Gerard Snaauw, Andrew P. Bradley, Ian D. Reid, Gustavo Carneiro

Proceedings of the 16th IEEE International Symposium on Biomedical Imaging, 2019

Producing Radiologist-Quality Reports for Interpretable Deep Learning.

William Gale, Luke Oakden-Rayner, Gustavo Carneiro, Lyle J. Palmer, Andrew P. Bradley

Proceedings of the 16th IEEE International Symposium on Biomedical Imaging, 2019

Deep Reinforcement Learning for Detecting Breast Lesions from DCE-MRI.

Gabriel Maicas, Andrew P. Bradley, Jacinto C. Nascimento, Ian D. Reid, Gustavo Carneiro

Proceedings of the Deep Learning and Convolutional Neural Networks for Medical Imaging and Clinical Informatics, 2019

2018

Is the winner really the best? A critical analysis of common research practice in biomedical image analysis competitions.

Lena Maier-Hein, Matthias Eisenmann, Annika Reinke, Sinan Onogur, Marko Stankovic, Patrick Scholz, Tal Arbel, Hrvoje Bogunovic, Andrew P. Bradley, Aaron Carass, Carolin Feldmann, Alejandro F. Frangi, Peter M. Full, Bram van Ginneken, Allan Hanbury, Katrin Honauer, Michal Kozubek, Bennett A. Landman, Keno März, Oskar Maier, Klaus H. Maier-Hein, Bjoern H. Menze, Henning Müller, Peter F. Neher, Wiro J. Niessen, Nasir M. Rajpoot, Gregory C. Sharp, Korsuk Sirinukunwattana, Stefanie Speidel, Christian Stock, Danail Stoyanov, Abdel Aziz Taha, Fons van der Sommen, Ching-Wei Wang, Marc-André Weber, Guoyan Zheng, Pierre Jannin, Annette Kopp-Schneider

CoRR, 2018

Producing radiologist-quality reports for interpretable artificial intelligence.

William Gale, Luke Oakden-Rayner, Gustavo Carneiro, Andrew P. Bradley, Lyle J. Palmer

CoRR, 2018

1st MICCAI workshop on deep learning in medical image analysis.

Gustavo Carneiro, João Manuel R. S. Tavares, Andrew P. Bradley, João Paulo Papa, Jacinto C. Nascimento, Jaime S. Cardoso, Zhi Lu, Vasileios Belagiannis

Comput. methods Biomech. Biomed. Eng. Imaging Vis., 2018

How to Exploit Weaknesses in Biomedical Challenge Design and Organization.

Annika Reinke, Matthias Eisenmann, Sinan Onogur, Marko Stankovic, Patrick Scholz, Peter M. Full, Hrvoje Bogunovic, Bennett A. Landman, Oskar Maier, Bjoern H. Menze, Gregory C. Sharp, Korsuk Sirinukunwattana, Stefanie Speidel, Fons van der Sommen, Guoyan Zheng, Henning Müller, Michal Kozubek, Tal Arbel, Andrew P. Bradley, Pierre Jannin, Annette Kopp-Schneider, Lena Maier-Hein

Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2018, 2018

Training Medical Image Analysis Systems like Radiologists.

Gabriel Maicas, Andrew P. Bradley, Jacinto C. Nascimento, Ian D. Reid, Gustavo Carneiro

Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2018, 2018

2017

Combining Deep Learning and Structured Prediction for Segmenting Masses in Mammograms.

Neeraj Dhungel, Gustavo Carneiro, Andrew P. Bradley

Proceedings of the Deep Learning and Convolutional Neural Networks for Medical Image Computing, 2017

Automated Analysis of Unregistered Multi-View Mammograms With Deep Learning.

Gustavo Carneiro, Jacinto C. Nascimento, Andrew P. Bradley

IEEE Trans. Medical Imaging, 2017

Evaluation of Three Algorithms for the Segmentation of Overlapping Cervical Cells.

Zhi Lu, Gustavo Carneiro, Andrew P. Bradley, Daniela Ushizima, Masoud S. Nosrati, Andrea G. C. Bianchi, Cláudia M. Carneiro, Ghassan Hamarneh

IEEE J. Biomed. Health Informatics, 2017

A deep learning approach for the analysis of masses in mammograms with minimal user intervention.

Neeraj Dhungel, Gustavo Carneiro, Andrew P. Bradley

Medical Image Anal., 2017

Detecting hip fractures with radiologist-level performance using deep neural networks.

William Gale, Luke Oakden-Rayner, Gustavo Carneiro, Andrew P. Bradley, Lyle J. Palmer

CoRR, 2017

Deep Reinforcement Learning for Active Breast Lesion Detection from DCE-MRI.

Gabriel Maicas, Gustavo Carneiro, Andrew P. Bradley, Jacinto C. Nascimento, Ian D. Reid

Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2017, 2017

Multi-scale mass segmentation for mammograms via cascaded random forests.

Hang Min, Shekhar S. Chandra, Neeraj Dhungel, Stuart Crozier, Andrew P. Bradley

Proceedings of the 14th IEEE International Symposium on Biomedical Imaging, 2017

Globally optimal breast mass segmentation from DCE-MRI using deep semantic segmentation as shape prior.

Gabriel Maicas, Gustavo Carneiro, Andrew P. Bradley

Proceedings of the 14th IEEE International Symposium on Biomedical Imaging, 2017

Fully automated classification of mammograms using deep residual neural networks.

Neeraj Dhungel, Gustavo Carneiro, Andrew P. Bradley

Proceedings of the 14th IEEE International Symposium on Biomedical Imaging, 2017

Automated 5-year mortality prediction using deep learning and radiomics features from chest computed tomography.

Gustavo Carneiro, Luke Oakden-Rayner, Andrew P. Bradley, Jacinto C. Nascimento, Lyle J. Palmer

Proceedings of the 14th IEEE International Symposium on Biomedical Imaging, 2017

Mass segmentation in mammograms: A cross-sensor comparison of deep and tailored features.

Jaime S. Cardoso, Nuno Marques, Neeraj Dhungel, Gustavo Carneiro, Andrew P. Bradley

Proceedings of the 2017 IEEE International Conference on Image Processing, 2017

Deep Learning Models for Classifying Mammogram Exams Containing Unregistered Multi-View Images and Segmentation Maps of Lesions1.

Gustavo Carneiro, Jacinto C. Nascimento, Andrew P. Bradley

Proceedings of the Deep Learning for Medical Image Analysis, 1st Edition, 2017

2016

Automated Detection of Individual Micro-calcifications from Mammograms using a Multi-stage Cascade Approach.

Zhi Lu, Gustavo Carneiro, Neeraj Dhungel, Andrew P. Bradley

CoRR, 2016

The Automated Learning of Deep Features for Breast Mass Classification from Mammograms.

Neeraj Dhungel, Gustavo Carneiro, Andrew P. Bradley

Proceedings of the Medical Image Computing and Computer-Assisted Intervention - MICCAI 2016, 2016

2015

An Improved Joint Optimization of Multiple Level Set Functions for the Segmentation of Overlapping Cervical Cells.

Zhi Lu, Gustavo Carneiro, Andrew P. Bradley

IEEE Trans. Image Process., 2015

Segmentation of skin strata in reflectance confocal microscopy depth stacks.

Samuel C. Hames, Marco Ardigò, H. Peter Soyer, Andrew P. Bradley, Tarl W. Prow

Proceedings of the Medical Imaging 2015: Image Processing, 2015

Deep Learning and Structured Prediction for the Segmentation of Mass in Mammograms.

Neeraj Dhungel, Gustavo Carneiro, Andrew P. Bradley

Proceedings of the Medical Image Computing and Computer-Assisted Intervention - MICCAI 2015, 2015

Unregistered Multiview Mammogram Analysis with Pre-trained Deep Learning Models.

Gustavo Carneiro, Jacinto C. Nascimento, Andrew P. Bradley

Proceedings of the Medical Image Computing and Computer-Assisted Intervention - MICCAI 2015 - 18th International Conference Munich, Germany, October 5, 2015

Tree RE-weighted belief propagation using deep learning potentials for mass segmentation from mammograms.

Neeraj Dhungel, Gustavo Carneiro, Andrew P. Bradley

Proceedings of the 12th IEEE International Symposium on Biomedical Imaging, 2015

Deep structured learning for mass segmentation from mammograms.

Neeraj Dhungel, Gustavo Carneiro, Andrew P. Bradley

Proceedings of the 2015 IEEE International Conference on Image Processing, 2015

Spikes from compound action potentials in simulated microelectrode recordings.

Kristian J. Weegink, John J. Varghese, Andrew P. Bradley

Proceedings of the 2015 IEEE International Conference on Acoustics, 2015

Spectral properties of neuronal pulse interval modulation.

John J. Varghese, Kristian J. Weegink, P. A. Bellette, Andrew P. Bradley

Proceedings of the 2015 IEEE International Conference on Acoustics, 2015

Multiple instance learning for breast MRI based on generic spatio-temporal features.

Fahira Afzal Maken, Andrew P. Bradley

Proceedings of the 2015 IEEE International Conference on Acoustics, 2015

Expectation-Maximization with Image-Weighted Markov Random Fields to Handle Severe Pathology.

Alex M. Pagnozzi, Nicholas D. H. Dowson, Andrew P. Bradley, Roslyn N. Boyd, Pierrick Bourgeat, Stephen E. Rose

Proceedings of the 2015 International Conference on Digital Image Computing: Techniques and Applications, 2015

Anatomical Skin Segmentation in Reflectance Confocal Microscopy with Weak Labels.

Samuel C. Hames, Marco Ardigò, H. Peter Soyer, Andrew P. Bradley, Tarl W. Prow

Proceedings of the 2015 International Conference on Digital Image Computing: Techniques and Applications, 2015

Automated Mass Detection in Mammograms Using Cascaded Deep Learning and Random Forests.

Neeraj Dhungel, Gustavo Carneiro, Andrew P. Bradley

Proceedings of the 2015 International Conference on Digital Image Computing: Techniques and Applications, 2015

2014

Half-AUC for the evaluation of sensitive or specific classifiers.

Andrew P. Bradley

Pattern Recognit. Lett., 2014

Extended Naïve Bayes for Group Based Classification.

Noor Azah Samsudin, Andrew P. Bradley

Proceedings of the Recent Advances on Soft Computing and Data Mining, 2014

Microscopic specimen delineation using auto-phase correlation index.

Yilun Fan, Yaniv Gal, Andrew P. Bradley

Proceedings of the IEEE 11th International Symposium on Biomedical Imaging, 2014

Characterization of movements during restless sleep in children: A pilot study.

Marnie L. Lamprecht, Philip Ian Terrill, Chloe L. Parsley, Andrew P. Bradley

Proceedings of the 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2014

Multiple Instance Learning for Breast Cancer Magnetic Resonance Imaging.

Fahira A. Maken, Yaniv Gal, Darryl McClymont, Andrew P. Bradley

Proceedings of the 2014 International Conference on Digital Image Computing: Techniques and Applications, 2014

2013

ROC curve equivalence using the Kolmogorov-Smirnov test.

Andrew P. Bradley

Pattern Recognit. Lett., 2013

Evaluation of a morphological filter in mean cardiac output determination: application to left ventricular assist devices.

Michael Charles Stevens, Andrew P. Bradley, Stephen J. Wilson, David G. Mason

Medical Biol. Eng. Comput., 2013

Automated Nucleus and Cytoplasm Segmentation of Overlapping Cervical Cells.

Zhi Lu, Gustavo Carneiro, Andrew P. Bradley

Proceedings of the Medical Image Computing and Computer-Assisted Intervention - MICCAI 2013, 2013

Effect of posterized naturalistic stimuli on SSVEP-based BCI.

Kian B. Ng, Andrew P. Bradley, Ross Cunnington

Proceedings of the 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2013

Performance Analysis of Three Microscope Slide Scanning Techniques.

Yilun Fan, Yaniv Gal, Andrew P. Bradley

Proceedings of the 2013 International Conference on Digital Image Computing: Techniques and Applications, 2013

Illumination Effects in Quantitative Virtual Microscopy.

Doreen Altinay, Andrew P. Bradley

Proceedings of the Computer Analysis of Images and Patterns, 2013

2012

Enhancing the classification accuracy of Steady-State Visual Evoked Potential-based Brain-Computer Interface using Component Synchrony Measure.

Kian B. Ng, Ross Cunnington, Andrew P. Bradley

Proceedings of the 2012 International Joint Conference on Neural Networks (IJCNN), 2012

A Comparison of Multiple Instance and Group Based Learning.

Steven D. Brossi, Andrew P. Bradley

Proceedings of the 2012 International Conference on Digital Image Computing Techniques and Applications, 2012

2011

Effect of competing stimuli on SSVEP-based BCI.

Kian B. Ng, Andrew P. Bradley, Ross Cunnington

Proceedings of the 33rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2011

An Evaluation of Multi-resolution Microscope Slide Scanning Algorithms.

Doreen Altinay, Andrew P. Bradley

Proceedings of the 2011 International Conference on Digital Image Computing: Techniques and Applications (DICTA), 2011

Investigation of the non-Markovity Spectrum as a Cognitive Processing Measure of Deep Brain Microelectrode Recordings.

P. A. Meehan, P. A. Bellette, Andrew P. Bradley, J. E. Castner, Helen J. Chenery, David A. Copland, John J. Varghese, Terry Coyne, P. A. Silburn

Proceedings of the BIOSIGNALS 2011, 2011

2010

Denoising of Dynamic Contrast-Enhanced MR Images Using Dynamic Nonlocal Means.

Yaniv Gal, Andrew Mehnert, Andrew P. Bradley, Kerry McMahon, Dominic Kennedy, Stuart Crozier

IEEE Trans. Medical Imaging, 2010

Intelligible support vector machines for diagnosis of diabetes mellitus.

Nahla H. Barakat, Andrew P. Bradley, Mohamed Nabil H. Barakat

IEEE Trans. Inf. Technol. Biomed., 2010

Nearest neighbour group-based classification.

Noor Azah Samsudin, Andrew P. Bradley

Pattern Recognit., 2010

Rule extraction from support vector machines: A review.

Nahla H. Barakat, Andrew P. Bradley

Neurocomputing, 2010

On the Estimation of Extrinsic and Intrinsic Parameters of Optical Microscope Calibration.

Doreen Altinay, Andrew P. Bradley, Andrew Mehnert

Proceedings of the International Conference on Digital Image Computing: Techniques and Applications, 2010

2009

The Effect of Domain Knowledge on Rule Extraction from Support Vector Machines.

Nahla H. Barakat, Andrew P. Bradley

Proceedings of the Machine Learning and Data Mining in Pattern Recognition, 2009

Feature and Classifier Selection for Automatic Classification of Lesions in Dynamic Contrast-Enhanced MRI of the Breast.

Yaniv Gal, Andrew Mehnert, Andrew P. Bradley, Dominic Kennedy, Stuart Crozier

Proceedings of the DICTA 2009, 2009

2008

Group-based meta-classification.

Noor Azah Samsudin, Andrew P. Bradley

Proceedings of the 19th International Conference on Pattern Recognition (ICPR 2008), 2008

Mixed content image compression by gradient field integration.

Peter W. M. Ilbery, David Taubman, Andrew P. Bradley

Proceedings of the International Conference on Image Processing, 2008

2007

Rule Extraction from Support Vector Machines: A Sequential Covering Approach.

Nahla H. Barakat, Andrew P. Bradley

IEEE Trans. Knowl. Data Eng., 2007

Correspondence-Free Determination of the Affine Fundamental Matrix.

Stefan Lehmann, Andrew P. Bradley, I. Vaughan L. Clarkson, John Williams, Peter J. Kootsookos

IEEE Trans. Pattern Anal. Mach. Intell., 2007

A Comparison of DCT and DWT Block Based Watermarking on Medical Image Quality.

Jason Dowling, Birgit M. Planitz, Anthony J. Maeder, Jiang Du, Binh Pham, Colin Boyd, Shaokang Chen, Andrew P. Bradley, Stuart Crozier

Proceedings of the Digital Watermarking, 6th International Workshop, 2007

Automatic Segmentation of Enhancing Breast Tissue in Dynamic Contrast-Enhanced MR Images.

Yaniv Gal, Andrew Mehnert, Andrew P. Bradley, Kerry McMahon, Stuart Crozier

Proceedings of the International Conference on Digital Image Computing: Techniques and Applications, 2007

2006

Rule Extraction from Support Vector Machines: Measuring the Explanation Capability Using the Area under the ROC Curve.

Nahla H. Barakat, Andrew P. Bradley

Proceedings of the 18th International Conference on Pattern Recognition (ICPR 2006), 2006

Estimation Of Epipolar Geometry Via The Radon Transform.

Stefan Lehmann, Andrew P. Bradley, I. Vaughan L. Clarkson

Proceedings of the 2006 IEEE International Conference on Acoustics Speech and Signal Processing, 2006

2005

Virtual Microscopy with Extended Depth of Field.

Andrew P. Bradley, Michael Wildermoth, Paul Mills

Proceedings of the International Conference on Digital Image Computing: Techniques and Applications, 2005

Towards Optimal Image Stitching for Virtual Microscopy.

Ben Appleton, Andrew P. Bradley, Michael Wildermoth

Proceedings of the International Conference on Digital Image Computing: Techniques and Applications, 2005

2004

Sample Size Estimation using the Receiver Operating Characteristic Curve.

Andrew P. Bradley, I. Dennis Longstaff

Proceedings of the 17th International Conference on Pattern Recognition, 2004

2003

Visual attention for region of interest coding in JPEG 2000.

Andrew P. Bradley, Fred Stentiford

J. Vis. Commun. Image Represent., 2003

Shift-invariance in the Discrete Wavelet Transform.

Andrew P. Bradley

Proceedings of the Seventh International Conference on Digital Image Computing: Techniques and Applications, 2003

1999

A wavelet visible difference predictor.

Andrew P. Bradley

IEEE Trans. Image Process., 1999

1998

Perceptual quality metrics applied to still image compression.

Michael P. Eckert, Andrew P. Bradley

Signal Process., 1998

1997

The use of the area under the ROC curve in the evaluation of machine learning algorithms.

Andrew P. Bradley

Pattern Recognit., 1997

1996

Machine learning for medical diagnostics: techniques for feature extraction, classification, and evaluation

Andrew P. Bradley

PhD thesis, 1996

ROC curves and the X² test.

Andrew P. Bradley

Pattern Recognit. Lett., 1996

The Multiscale Classifier.

Brian C. Lovell, Andrew P. Bradley

IEEE Trans. Pattern Anal. Mach. Intell., 1996