Big Universe, Big Data: Machine Learning and Image Analysis for Astronomy von Kremer, Jan, Stensbo-Smidt, Kristoffer, Gieseke, Fabian, Pedersen, Kim Steenstrup, Igel, Christian

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Interesting Interest Points: A Comparative Study of Interest Point Performance on a Unique Data Set von Aanæs, Henrik, Dahl, Anders Lindbjerg, Steenstrup Pedersen, Kim

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Active learning with support vector machines von Kremer, Jan, Steenstrup Pedersen, Kim, Igel, Christian

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Sacrificing information for the greater good: how to select photometric bands for optimal accuracy von Stensbo-Smidt, Kristoffer, Gieseke, Fabian, Igel, Christian, Zirm, Andrew, Pedersen, Kim Steenstrup

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Unscented Kalman Filtering on Riemannian Manifolds von Hauberg, Søren, Lauze, François, Pedersen, Kim Steenstrup

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Special section on 19th Scandinavian conference on image analysis (SCIA 2015) von Steenstrup Pedersen, Kim, Paulsen, Rasmus R.

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Erratum to: Interesting Interest Points: A Comparative Study of Interest Point Performance on a Unique Data Set von Aanæs, Henrik, Dahl, Anders Lindbjerg, Steenstrup Pedersen, Kim

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Refractive Pose Refinement von Hu, Xiao, Lauze, François, Pedersen, Kim Steenstrup

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Image Analysis: 19th Scandinavian Conference, SCIA 2015, Copenhagen, Denmark, June 15-17, 2015. Proceedings von Paulsen, Rasmus R, Pedersen, Kim S

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Refractive Pose Refinement: Generalising the Geometric Relation between Camera and Refractive Interface von Hu, Xiao, Lauze, François, Pedersen, Kim Steenstrup

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Integrating Deep Learning Derived Morphological Traits and Molecular Data for Total-Evidence Phylogenetics: Lessons from Digitized Collections von Hunt, Roberta, Reyes-Hernández, José L, Shaw, Josh Jenkins, Solodovnikov, Alexey, Pedersen, Kim Steenstrup

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Field of Particle Filters for Image Inpainting von Cuzol, Anne, Pedersen, Kim Steenstrup, Nielsen, Mads

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Rove-Tree-11: The Not-so-Wild Rover a Hierarchically Structured Image Dataset for Deep Metric Learning Research von Hunt, Roberta, Pedersen, Kim Steenstrup

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Hyperspectral imaging for classification of bulk grain samples with deep convolutional neural networks von Dreier, Erik Schou, Sorensen, Klavs Martin, Lund-Hansen, Toke, Jespersen, Birthe Møller, Pedersen, Kim Steenstrup

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IKPLS: Improved Kernel Partial Least Squares and Fast Cross-Validation Algorithms for Python with CPU and GPU Implementations Using NumPy and JAX von Engstrøm, Ole-Christian Galbo, Dreier, Erik Schou, Jespersen, Birthe Møller, Pedersen, Kim Steenstrup

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Predicting Articulated Human Motion from Spatial Processes von Hauberg, Søren, Pedersen, Kim Steenstrup

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Spatial Measures between Human Poses for Classification and Understanding von Hauberg, Søren, Steenstrup Pedersen, Kim

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Natural metrics and least-committed priors for articulated tracking von Hauberg, Søren, Sommer, Stefan, Pedersen, Kim Steenstrup

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The Phantom of the Elytra -- Phylogenetic Trait Extraction from Images of Rove Beetles Using Deep Learning -- Is the Mask Enough? von Hunt, Roberta, Pedersen, Kim Steenstrup

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Big Universe, Big Data: Machine Learning and Image Analysis for Astronomy von Kremer, Jan, Stensbo-Smidt, Kristoffer, Gieseke, Fabian, Kim Steenstrup Pedersen, Igel, Christian

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