Fabian Gieseke

ORCID

Publication Activity (10 Years)

Years Active: 2009-2024
Publications (10 Years): 48

Top Venues

Carl von Ossietzky University of Oldenburg (PHD)

Education History

Carl von Ossietzky University of Oldenburg

PHD

Publications

Christian Lülf, Denis Mayr Lima Martins, Marcos Antonio Vaz Salles, Yongluan Zhou, Fabian Gieseke
CLIP-Branches: Interactive Fine-Tuning for Text-Image Retrieval. CoRR (2024)
Jan Pauls, Max Zimmer, Una M. Kelly, Martin Schwartz, Sassan Saatchi, Philippe Ciais, Sebastian Pokutta, Martin Brandt, Fabian Gieseke
Estimating Canopy Height at Scale. CoRR (2024)
Denis Mayr Lima Martins, Christian Lülf, Fabian Gieseke
Training neural networks end-to-end for hyperbox-based classification. Neurocomputing 599 (2024)
Christian Lülf, Denis Mayr Lima Martins, Marcos Antonio Vaz Salles, Yongluan Zhou, Fabian Gieseke
Interactive Fine-Tuning for Text-Image Retrieval. SIGIR (2024)
Lei Li, Tianfang Zhang, Stefan Oehmcke, Fabian Gieseke, Christian Igel
BuildSeg: A General Framework for the Segmentation of Buildings. CoRR (2023)
Christian Lülf, Denis Mayr Lima Martins, Marcos Antonio Vaz Salles, Yongluan Zhou, Fabian Gieseke
RapidEarth: A Search-by-Classification Engine for Large-Scale Geospatial Imagery. CoRR (2023)
Denis Mayr Lima Martins, Christian Lülf, Fabian Gieseke
End-to-End Neural Network Training for Hyperbox-Based Classification. CoRR (2023)
Christian Lülf, Denis Mayr Lima Martins, Marcos Antonio Vaz Salles, Yongluan Zhou, Fabian Gieseke
Fast Search-By-Classification for Large-Scale Databases Using Index-Aware Decision Trees and Random Forests. Proc. VLDB Endow. 16 (11) (2023)
Christian Lülf, Denis Mayr Lima Martins, Marcos Antonio Vaz Salles, Yongluan Zhou, Fabian Gieseke
RapidEarth: A Search-by-Classification Engine for Large-Scale Geospatial Imagery. SIGSPATIAL/GIS (2023)
Denis Martins, Christian Lülf, Fabian Gieseke
End-to-End Neural Network Training for Hyperbox-Based Classification. ESANN (2023)
Christian Lülf, Denis Mayr Lima Martins, Marcos Antonio Vaz Salles, Yongluan Zhou, Fabian Gieseke
Fast Search-By-Classification for Large-Scale Databases Using Index-Aware Decision Trees and Random Forests. CoRR (2023)
Dmitry Serykh, Stefan Oehmcke, Cosmin E. Oancea, Dainius Masiliunas, Jan Verbesselt, Yan Cheng, Stéphanie Horion, Fabian Gieseke, Nikolaj Hinnerskov
Seasonal-Trend Time Series Decomposition on Graphics Processing Units. BigData (2023)
Lei Li, Tianfang Zhang, Stefan Oehmcke, Fabian Gieseke, Christian Igel
Mask-FPAN: Semi-Supervised Face Parsing in the Wild With De-Occlusion and UV GAN. CoRR (2022)
Tianfang Zhang, Lei Li, Christian Igel, Stefan Oehmcke, Fabian Gieseke, Zhenming Peng
LR-CSNet: Low-Rank Deep Unfolding Network for Image Compressive Sensing. CoRR (2022)
Stefan Oehmcke, Fabian Gieseke
Input Selection for Bandwidth-Limited Neural Network Inference. SDM (2022)
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)
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) (2022)
Stefan Oehmcke, Thomas Nyegaard-Signori, Kenneth Grogan, Fabian Gieseke
Estimating Forest Canopy Height With Multi-Spectral and Multi-Temporal Imagery Using Deep Learning. IEEE BigData (2021)
Stefan Oehmcke, Lei Li, Jaime Revenga, Thomas Nord-Larsen, Katerina Trepekli, Fabian Gieseke, Christian Igel
Deep Learning Based 3D Point Cloud Regression for Estimating Forest Biomass. CoRR (2021)
Philip Munksgaard, Svend Lund Breddam, Troels Henriksen, Fabian Gieseke, Cosmin E. Oancea
Dataset Sensitive Autotuning of Multi-versioned Code Based on Monotonic Properties - Autotuning in Futhark. TFP (2021)
Yimian Dai, Fabian Gieseke, Stefan Oehmcke, Yiquan Wu, Kobus Barnard
Attentional Feature Fusion. WACV (2021)
Cosmin Eugen Oancea, Ties Robroek, Fabian Gieseke
Approximate Nearest-Neighbour Fields via Massively-Parallel Propagation-Assisted K-D Trees. IEEE BigData (2020)
Eliakim Hamunyela, Sabina Rosca, Andrei Mirt, Eric Engle, Martin Herold, Fabian Gieseke, Jan Verbesselt
Implementation of BFASTmonitor Algorithm on Google Earth Engine to Support Large-Area and Sub-Annual Change Monitoring Using Earth Observation Data. Remote. Sens. 12 (18) (2020)
Nikita Moriakov, Ashwin Samudre, Michela Negro, Fabian Gieseke, Sydney Otten, Luc Hendriks
Inferring astrophysical X-ray polarization with deep learning. CoRR (2020)
Fabian Gieseke, Sabina Rosca, Troels Henriksen, Jan Verbesselt, Cosmin E. Oancea
Massively-Parallel Change Detection for Satellite Time Series Data with Missing Values. ICDE (2020)
Yimian Dai, Stefan Oehmcke, Fabian Gieseke, Yiquan Wu, Kobus Barnard
Attention as Activation. ICPR (2020)
Stefan Oehmcke, Tzu-Hsin Karen Chen, Alexander V. Prishchepov, Fabian Gieseke
Creating cloud-free satellite imagery from image time series with deep learning. BigSpatial@SIGSPATIAL (2020)
Yimian Dai, Fabian Gieseke, Stefan Oehmcke, Yiquan Wu, Kobus Barnard
Attentional Feature Fusion. CoRR (2020)
Stefan Oehmcke, Christoffer Thrysøe, Andreas Borgstad, Marcos Antonio Vaz Salles, Martin Brandt, Fabian Gieseke
Detecting Hardly Visible Roads in Low-Resolution Satellite Time Series Data. CoRR (2019)
Stefan Oehmcke, Christoffer Thrysøe, Andreas Borgstad, Marcos Antonio Vaz Salles, Martin Brandt, Fabian Gieseke
Detecting Hardly Visible Roads in Low-Resolution Satellite Time Series Data. IEEE BigData (2019)
Vinnie Ko, Stefan Oehmcke, Fabian Gieseke
Magnitude and Uncertainty Pruning Criterion for Neural Networks. IEEE BigData (2019)
Stefan Oehmcke, Fabian Gieseke
Learning Selection Masks for Deep Neural Networks. CoRR (2019)
Vinnie Ko, Stefan Oehmcke, Fabian Gieseke
Magnitude and Uncertainty Pruning Criterion for Neural Networks. CoRR (2019)
Malte von Mehren, Fabian Gieseke, Jan Verbesselt, Sabina Rosca, Stéphanie Horion, Achim Zeileis
Massively-parallel break detection for satellite data. SSDBM (2018)
Corneliu Florea, Fabian Gieseke
Artistic movement recognition by consensus of boosted SVM based experts. J. Vis. Commun. Image Represent. 56 (2018)
Fabian Gieseke, Cosmin Eugen Oancea, Ashish Mahabal, Christian Igel, Tom Heskes
Bigger Buffer k-d Trees on Multi-Many-Core Systems. VECPAR (2018)
Fabian Gieseke, Christian Igel
Training Big Random Forests with Little Resources. CoRR (2018)
Malte von Mehren, Fabian Gieseke, Jan Verbesselt, Sabina Rosca, Stéphanie Horion, Achim Zeileis
Massively-Parallel Break Detection for Satellite Data. CoRR (2018)
Fabian Gieseke, Christian Igel
Training Big Random Forests with Little Resources. KDD (2018)
Fabian Gieseke, Kai Lars Polsterer, Ashish Mahabal, Christian Igel, Tom Heskes
Massively-parallel best subset selection for ordinary least-squares regression. SSCI (2017)
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) (2017)
Corneliu Florea, Cosmin Toca, Fabian Gieseke
Artistic Movement Recognition by Boosted Fusion of Color Structure and Topographic Description. WACV (2017)
Ashish Mahabal, Kshiteej Sheth, Fabian Gieseke, A. Pai, S. George Djorgovski, Andrew J. Drake, Matthew J. Graham
Deep-learnt classification of light curves. SSCI (2017)
Jan Kremer, Kristoffer Stensbo-Smidt, Fabian Gieseke, Kim Steenstrup Pedersen, Christian Igel
Big Universe, Big Data: Machine Learning and Image Analysis for Astronomy. CoRR (2017)
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 (2017)
Ashish Mahabal, Kshiteej Sheth, Fabian Gieseke, Akshay Pai, S. George Djorgovski, Andrew J. Drake, Matthew J. Graham
Deep-Learnt Classification of Light Curves. CoRR (2017)
Kai Lars Polsterer, Fabian Gieseke, Christian Igel, Bernd Doser, Nikolaos Gianniotis
Parallelized rotation and flipping INvariant Kohonen maps (PINK) on GPUs. ESANN (2016)
Emille E. O. Ishida, Michele Sasdelli, Ricardo Vilalta, Michel Aguena, Vinicius C. Busti, Hugo Camacho, Arlindo M. M. Trindade, Fabian Gieseke, Rafael S. de Souza, Yabebal T. Fantaye, Paolo A. Mazzali
Exploring the spectroscopic diversity of type Ia supernovae with Deep Learning and Unsupervised Clustering. Astroinformatics (2016)
Fabian Gieseke, Cosmin Eugen Oancea, Ashish Mahabal, Christian Igel, Tom Heskes
Bigger Buffer k-d Trees on Multi-Many-Core Systems. CoRR (2015)
Fabian Gieseke
An Efficient Many-Core Implementation for Semi-Supervised Support Vector Machines. MOD (2015)
Fabian Gieseke, Tapio Pahikkala, Tom Heskes
Batch Steepest-Descent-Mildest-Ascent for Interactive Maximum Margin Clustering. IDA (2015)
Jan Kremer, Fabian Gieseke, Kim Steenstrup Pedersen, Christian Igel
Nearest neighbor density ratio estimation for large-scale applications in astronomy. Astron. Comput. 12 (2015)
Oliver Kramer, Fabian Gieseke, Justin Heinermann, Jendrik Poloczek, Nils André Treiber
A Framework for Data Mining in Wind Power Time Series. DARE (2014)
Fabian Gieseke, Justin Heinermann, Cosmin E. Oancea, Christian Igel
Buffer k-d Trees: Processing Massive Nearest Neighbor Queries on GPUs. ICML (2014)
Tapio Pahikkala, Antti Airola, Fabian Gieseke, Oliver Kramer
On Unsupervised Training of Multi-Class Regularized Least-Squares Classifiers. J. Comput. Sci. Technol. 29 (1) (2014)
Fabian Gieseke, Antti Airola, Tapio Pahikkala, Oliver Kramer
Fast and simple gradient-based optimization for semi-supervised support vector machines. Neurocomputing 123 (2014)
Fabian Gieseke, Kai Lars Polsterer, Cosmin Eugen Oancea, Christian Igel
Speedy greedy feature selection: Better redshift estimation via massive parallelism. ESANN (2014)
Oliver Kramer, Fabian Gieseke, Benjamin Satzger
Wind energy prediction and monitoring with neural computation. Neurocomputing 109 (2013)
Fabian Gieseke, Tapio Pahikkala, Christian Igel
Polynomial Runtime Bounds for Fixed-Rank Unsupervised Least-Squares Classification. ACML (2013)
Oliver Kramer, Nils André Treiber, Fabian Gieseke
Support Vector Machines for Wind Energy Prediction in Smart Grids. EnviroInfo (2013)
Justin Heinermann, Oliver Kramer, Kai Lars Polsterer, Fabian Gieseke
On GPU-Based Nearest Neighbor Queries for Large-Scale Photometric Catalogs in Astronomy. KI (2013)
Oliver Kramer, Fabian Gieseke, Kai Lars Polsterer
Learning morphological maps of galaxies with unsupervised regression. Expert Syst. Appl. 40 (8) (2013)
Fabian Gieseke, Oliver Kramer
Towards Non-linear Constraint Estimation for Expensive Optimization. EvoApplications (2013)
Fabian Gieseke
From Supervised to Unsupervised Support Vector Machines and Applications in Astronomy. Künstliche Intell. 27 (3) (2013)
Fabian Gieseke, Gabriel Moruz, Jan Vahrenhold
-means in space revisited. Frontiers Comput. Sci. 6 (2) (2012)
Oliver Kramer, Fabian Gieseke
Evolutionary kernel density regression. Expert Syst. Appl. 39 (10) (2012)
Fabian Gieseke, Antti Airola, Tapio Pahikkala, Oliver Kramer
Sparse Quasi-Newton Optimization for Semi-supervised Support Vector Machines. ICPRAM (1) (2012)
Fabian Gieseke, Oliver Kramer, Antti Airola, Tapio Pahikkala
Efficient recurrent local search strategies for semi- and unsupervised regularized least-squares classification. Evol. Intell. 5 (3) (2012)
Fabian Gieseke
Von überwachten zu unüberwachten Support-Vektor-Maschinen und Anwendungen in der Astronomie. Ausgezeichnete Informatikdissertationen (2012)
Tapio Pahikkala, Antti Airola, Fabian Gieseke, Oliver Kramer
Unsupervised Multi-class Regularized Least-Squares Classification. ICDM (2012)
Fabian Gieseke, Oliver Kramer, Antti Airola, Tapio Pahikkala
Speedy Local Search for Semi-Supervised Regularized Least-Squares. KI (2011)
Oliver Kramer, Fabian Gieseke
Short-Term Wind Energy Forecasting Using Support Vector Regression. SOCO (2011)
Oliver Kramer, Fabian Gieseke
Analysis of wind energy time series with kernel methods and neural networks. ICNC (2011)
Oliver Kramer, Fabian Gieseke
Variance Scaling for EDAs Revisited. KI (2011)
Fabian Gieseke, Kai Lars Polsterer, Andreas Thom, Peter Zinn, Dominik Bomanns, Ralf-Jurgen Dettmar, Oliver Kramer, Jan Vahrenhold
Detecting Quasars in Large-Scale Astronomical Surveys. ICMLA (2010)
Fabian Gieseke, Gabriel Moruz, Jan Vahrenhold
Resilient K-d Trees: K-Means in Space Revisited. ICDM (2010)
Fabian Gieseke, Joachim Gudmundsson, Jan Vahrenhold
Pruning spanners and constructing well-separated pair decompositions in the presence of memory hierarchies. J. Discrete Algorithms 8 (3) (2010)
Fabian Gieseke, Tapio Pahikkala, Oliver Kramer
Fast evolutionary maximum margin clustering. ICML (2009)

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Publication Activity (10 Years)

Top Topics

Top Venues

Fabian Gieseke