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ORCIDFabian Gieseke
- > Home > Persons > Fabian Gieseke
Publications
- 2023
[i16]Lei Li, Tianfang Zhang, Stefan Oehmcke, Fabian Gieseke, Christian Igel:
BuildSeg: A General Framework for the Segmentation of Buildings. CoRR abs/2301.06190 (2023)- 2022
- [j15]Jaime C. Revenga, Katerina Trepekli
, Stefan Oehmcke, Rasmus Jensen, Lei Li, Christian Igel, Fabian Gieseke, Thomas Friborg:
Above-Ground Biomass Prediction for Croplands at a Sub-Meter Resolution Using UAV-LiDAR and Machine Learning Methods. Remote. Sens. 14(16): 3912 (2022) - [c37]Stefan Oehmcke, Lei Li, Jaime C. Revenga, Thomas Nord-Larsen, Katerina Trepekli, Fabian Gieseke, Christian Igel:
Deep learning based 3D point cloud regression for estimating forest biomass. SIGSPATIAL/GIS 2022: 38:1-38:4 - [i12]Tianfang Zhang, Lei Li, Christian Igel, Stefan Oehmcke, Fabian Gieseke, Zhenming Peng:
LR-CSNet: Low-Rank Deep Unfolding Network for Image Compressive Sensing. CoRR abs/2212.09088 (2022) - 2021
- [i11]Stefan Oehmcke, Lei Li, Jaime C. Revenga, Thomas Nord-Larsen, Katerina Trepekli, Fabian Gieseke, Christian Igel:
Deep Learning Based 3D Point Cloud Regression for Estimating Forest Biomass. CoRR abs/2112.11335 (2021) - 2018
- [c26]Fabian Gieseke, Christian Igel:
Training Big Random Forests with Little Resources. KDD 2018: 1445-1454 - [c24]Fabian Gieseke, Cosmin Eugen Oancea, Ashish Mahabal, Christian Igel, Tom Heskes:
Bigger Buffer k-d Trees on Multi-Many-Core Systems. VECPAR 2018: 202-214 - [i5]Fabian Gieseke, Christian Igel:
Training Big Random Forests with Little Resources. CoRR abs/1802.06394 (2018) - 2017
- [j12]Jan Kremer, Kristoffer Stensbo-Smidt, Fabian Gieseke, Kim Steenstrup Pedersen, Christian Igel:
Big Universe, Big Data: Machine Learning and Image Analysis for Astronomy. IEEE Intell. Syst. 32(2): 16-22 (2017) - [j11]Fabian Gieseke, Cosmin E. Oancea, Christian Igel:
bufferkdtree: A Python library for massive nearest neighbor queries on multi-many-core devices. Knowl. Based Syst. 120: 1-3 (2017) - [c23]Fabian Gieseke, Kai Lars Polsterer, Ashish Mahabal, Christian Igel, Tom Heskes:
Massively-parallel best subset selection for ordinary least-squares regression. SSCI 2017: 1-8 - [i3]Jan Kremer, Kristoffer Stensbo-Smidt, Fabian Gieseke, Kim Steenstrup Pedersen, Christian Igel:
Big Universe, Big Data: Machine Learning and Image Analysis for Astronomy. CoRR abs/1704.04650 (2017) - 2016
- [c19]Kai Lars Polsterer, Fabian Gieseke, Christian Igel, Bernd Doser, Nikolaos Gianniotis:
Parallelized rotation and flipping INvariant Kohonen maps (PINK) on GPUs. ESANN 2016 - 2015
- [j10]Jan Kremer, Fabian Gieseke, Kim Steenstrup Pedersen, Christian Igel:
Nearest neighbor density ratio estimation for large-scale applications in astronomy. Astron. Comput. 12: 67-72 (2015) - [i1]Fabian Gieseke, Cosmin Eugen Oancea, Ashish Mahabal, Christian Igel, Tom Heskes:
Bigger Buffer k-d Trees on Multi-Many-Core Systems. CoRR abs/1512.02831 (2015) - 2014
- [c16]Fabian Gieseke, Kai Lars Polsterer, Cosmin Eugen Oancea, Christian Igel:
Speedy greedy feature selection: Better redshift estimation via massive parallelism. ESANN 2014 - [c15]Fabian Gieseke, Justin Heinermann, Cosmin E. Oancea, Christian Igel:
Buffer k-d Trees: Processing Massive Nearest Neighbor Queries on GPUs. ICML 2014: 172-180 - 2013
- [c13]Fabian Gieseke, Tapio Pahikkala, Christian Igel:
Polynomial Runtime Bounds for Fixed-Rank Unsupervised Least-Squares Classification. ACML 2013: 62-71
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