3D-modeling of deformed halite hopper crystals by Object Based Image Analysis
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Peter Hofmann | Christoph Leitner | Robert Marschallinger | P. Hofmann | C. Leitner | R. Marschallinger
[1] Anna Rotarska-Jagiela,et al. The corpus callosum in schizophrenia-volume and connectivity changes affect specific regions , 2008, NeuroImage.
[2] Shigeo Abe. Support Vector Machines for Pattern Classification , 2010, Advances in Pattern Recognition.
[3] A. Kendall,et al. Compaction in halite‐cemented carbonates – the Dawson Bay Formation (Middle Devonian) of Saskatchewan, Canada , 2000 .
[4] G. Meinel,et al. EVALUATION OF SEGMENTATION PROGRAMS FOR HIGH RESOLUTION REMOTE SENSING APPLICATIONS , 2003 .
[5] Norman Kerle,et al. 3D object-oriented image analysis in 3D geophysical modelling: Analysing the central part of the East African Rift System , 2015, Int. J. Appl. Earth Obs. Geoinformation.
[6] Dirk Tiede,et al. ESP: a tool to estimate scale parameter for multiresolution image segmentation of remotely sensed data , 2010, Int. J. Geogr. Inf. Sci..
[7] P. Jacobs,et al. Applications of X-ray computed tomography in the geosciences , 2003, Geological Society, London, Special Publications.
[8] Thomas Blaschke,et al. Geographic Information Science as a Common Cause for Interdisciplinary Research , 2012, AGILE Conf..
[9] Peter Hofmann,et al. Solid modeling of fossil small mammal teeth , 2011, Comput. Geosci..
[10] Maria Athelogou,et al. Cognition Network Technology – A Novel Multimodal Image Analysis Technique for Automatic Identification and Quantification of Biological Image Contents , 2007 .
[11] Susanne Nelskamp,et al. Dynamics of Complex Intracontinental Basins : The Central European Basin System , 2008 .
[12] Peter Hofmann,et al. Marble provenance designation with Object Based Image Analysis: State-of-the-art rock fabric characterization , 2013 .
[13] Arno Schäpe,et al. Multiresolution Segmentation : an optimization approach for high quality multi-scale image segmentation , 2000 .
[14] Dirk Gajewski,et al. Dynamics of Complex Intracontinental Basins , 2008 .
[15] Peter Norvig,et al. Artificial Intelligence: A Modern Approach , 1995 .
[16] Thomas Blaschke,et al. Land cover change assessment using decision trees, support vector machines and maximum likelihood classification algorithms , 2010, Int. J. Appl. Earth Obs. Geoinformation.
[17] Dirk Tiede,et al. Supervised and forest type-specific multi-scale segmentation for a one-level-representation of single trees , 2006 .
[18] Russell G. Congalton,et al. A review of assessing the accuracy of classifications of remotely sensed data , 1991 .
[19] R. Görgey,et al. Zur Kenntnis der Kalisalzlager von Wittelsheim im Ober-Elsaß , 1912 .
[20] I. Dan Melamed,et al. Precision and Recall of Machine Translation , 2003, NAACL.
[21] János Urai,et al. Flow and transport properties of salt rocks , 2005 .
[22] B. Charlotte Schreiber,et al. Displacive Halite Hoppers from the Dead Sea: Some Implications for Ancient Evaporite Deposits , 1981 .
[23] F. Neubauer,et al. Origin of deformed halite hopper crystals, pseudomorphic anhydrite cubes and polyhalite in Alpine evaporites (Austria, Germany) , 2012, International Journal of Earth Sciences.
[24] Xueliang Zhang,et al. Support vector machine-based decision tree for snow cover extraction in mountain areas using high spatial resolution remote sensing image , 2014 .
[25] Thomas Blaschke,et al. Geographic Object-Based Image Analysis – Towards a new paradigm , 2014, ISPRS journal of photogrammetry and remote sensing : official publication of the International Society for Photogrammetry and Remote Sensing.
[26] Anna Rotarska-Jagiela,et al. Automated segmentation of lateral ventricles from human and primate magnetic resonance images using cognition network technology. , 2006, Magnetic resonance imaging.
[27] Chih-Jen Lin,et al. A comparison of methods for multiclass support vector machines , 2002, IEEE Trans. Neural Networks.
[28] Peter A. Calabresi,et al. OASIS is Automated Statistical Inference for Segmentation, with applications to multiple sclerosis lesion segmentation in MRI☆ , 2013, NeuroImage: Clinical.
[29] Yunqian Ma,et al. Practical selection of SVM parameters and noise estimation for SVM regression , 2004, Neural Networks.
[30] R. Ketcham,et al. Acquisition, optimization and interpretation of X-ray computed tomographic imagery: applications to the geosciences , 2001 .
[31] S. Timmermanns,et al. The Challenge of Evidence-Based Medicine and Standardization in Health Care , 2003 .
[32] Stuart J. Russell,et al. Artificial Intelligence , 1986 .
[33] Kathleen C. Benison,et al. Sedimentology of Ancient Saline Pans: An Example from the Permian Opeche Shale, Williston Basin, North Dakota, U.S.A. , 2000 .
[34] Si Wu,et al. Improving support vector machine classifiers by modifying kernel functions , 1999, Neural Networks.
[35] Christian Igel,et al. Evolutionary tuning of multiple SVM parameters , 2005, ESANN.
[36] Russell G. Congalton,et al. Assessing the accuracy of remotely sensed data : principles and practices , 1998 .
[37] Russell Congalton,et al. Assessing the Accuracy of Remotely Sensed Data: Principles and Practices, Second Edition , 1998 .
[38] Thomas Blaschke,et al. Object based image analysis for remote sensing , 2010 .
[39] Sayan Mukherjee,et al. Choosing Multiple Parameters for Support Vector Machines , 2002, Machine Learning.
[40] Alexander Heidrich,et al. Automated Segmentation and Object Classification of CT Images: Application to In Vivo Molecular Imaging of Avian Embryos , 2013, Int. J. Biomed. Imaging.
[41] A. Tzotsos,et al. Support Vector Machine Classification for Object-Based Image Analysis , 2008 .
[42] Friedrich Frischknecht,et al. Imaging Cellular and Molecular Biological Functions , 2007 .
[43] W. Haidinger. Ueber die Pseudomorphosen nach Steinsalz , 1847 .