Topological modeling and classification of mammographic microcalcification clusters Z Chen, H Strange, A Oliver, ERE Denton, C Boggis, R Zwiggelaar IEEE transactions on biomedical engineering 62 (4), 1203-1214, 2014 | 108 | 2014 |
Texture segmentation using different orientations of GLCM features A Rampun, H Strange, R Zwiggelaar Proceedings of the 6th International Conference on Computer Vision/Computer …, 2013 | 55 | 2013 |
Modelling mammographic microcalcification clusters using persistent mereotopology H Strange, Z Chen, ERE Denton, R Zwiggelaar Pattern Recognition Letters 47, 157-163, 2014 | 42 | 2014 |
Open problems in spectral dimensionality reduction H Strange, R Zwiggelaar Springer International Publishing, 2014 | 41 | 2014 |
Automatic estimation of wheat grain morphometry from computed tomography data H Strange, R Zwiggelaar, C Sturrock, SJ Mooney, JH Doonan Functional Plant Biology 42 (5), 452-459, 2014 | 36 | 2014 |
A generalised solution to the out-of-sample extension problem in manifold learning H Strange, R Zwiggelaar Proceedings of the AAAI Conference on Artificial Intelligence 25 (1), 471-476, 2011 | 32 | 2011 |
Unsupervised cell nuclei segmentation based on morphology and adaptive active contour modelling Z Zeng, H Strange, C Han, R Zwiggelaar Image Analysis and Recognition: 10th International Conference, ICIAR 2013 …, 2013 | 8 | 2013 |
Myofibre segmentation in H&E stained adult skeletal muscle images using coherence-enhancing diffusion filtering H Strange, I Scott, R Zwiggelaar BMC Medical Imaging 14, 1-13, 2014 | 7 | 2014 |
Analysis of mammographic microcalcification clusters using topological features Z Chen, H Strange, E Denton, R Zwiggelaar Breast Imaging: 12th International Workshop, IWDM 2014, Gifu City, Japan …, 2014 | 7 | 2014 |
Meningioma subtype classification using morphology features and random forests H Strange, R Zwiggelaar Medical Imaging 2013: Digital Pathology 8676, 253-259, 2013 | 7 | 2013 |
Parallel projections for manifold learning H Strange, R Zwiggelaar 2010 Ninth International Conference on Machine Learning and Applications …, 2010 | 7 | 2010 |
Manifold learning for density segmentation in high risk mammograms H Strange, E Denton, M Kibiro, R Zwiggelaar Pattern Recognition and Image Analysis: 6th Iberian Conference, IbPRIA 2013 …, 2013 | 6 | 2013 |
Large Scale Data H Strange, R Zwiggelaar, H Strange, R Zwiggelaar Open Problems in Spectral Dimensionality Reduction, 69-81, 2014 | 5 | 2014 |
Fuzzy-entropy based image congealing N Mac Parthaláin, H Strange 2013 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), 1-8, 2013 | 5 | 2013 |
Classification performance related to intrinsic dimensionality in mammographic image analysis HG Strange, R Zwiggelaar Proceedings of the Thirteenth Annual Conference on Medical Image …, 2009 | 5 | 2009 |
Piecewise-linear manifold learning: A heuristic approach to non-linear dimensionality reduction H Strange, R Zwiggelaar Intelligent Data Analysis 19 (6), 1213-1232, 2015 | 3 | 2015 |
Spectral dimensionality reduction H Strange, R Zwiggelaar, H Strange, R Zwiggelaar Open Problems in Spectral Dimensionality Reduction, 7-22, 2014 | 3 | 2014 |
Intrinsic dimensionality H Strange, R Zwiggelaar, H Strange, R Zwiggelaar Open Problems in Spectral Dimensionality Reduction, 41-52, 2014 | 3 | 2014 |
Piecewise-Linear Manifold Learning H Strange Aberystwyth University, 2011 | 1 | 2011 |
Iterative hyperplane merging: A framework for manifold learning H Strange, R Zwiggelaar Science 4 (2), 87-99, 1989 | 1 | 1989 |