Fabian Gieseke

Neurocomputing, 2024

CLIP-Branches: Interactive Fine-Tuning for Text-Image Retrieval.

[BibT_eX]

[DOI]

CoRR, 2024

CLIP-Branches: Interactive Fine-Tuning for Text-Image Retrieval.

[BibT_eX]

[DOI]

Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2024

Estimating Canopy Height at Scale.

[BibT_eX]

[DOI]

Proceedings of the Forty-first International Conference on Machine Learning, 2024

2023

Fast Search-By-Classification for Large-Scale Databases Using Index-Aware Decision Trees and Random Forests.

[BibT_eX]

[DOI]

Proc. VLDB Endow., 2023

BuildSeg: A General Framework for the Segmentation of Buildings.

[BibT_eX]

[DOI]

CoRR, 2023

RapidEarth: A Search-by-Classification Engine for Large-Scale Geospatial Imagery.

[BibT_eX]

[DOI]

Proceedings of the 31st ACM International Conference on Advances in Geographic Information Systems, 2023

End-to-End Neural Network Training for Hyperbox-Based Classification.

[BibT_eX]

[DOI]

Denis Martins

Proceedings of the 31st European Symposium on Artificial Neural Networks, 2023

Seasonal-Trend Time Series Decomposition on Graphics Processing Units.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Conference on Big Data, 2023

2022

Above-Ground Biomass Prediction for Croplands at a Sub-Meter Resolution Using UAV-LiDAR and Machine Learning Methods.

[BibT_eX]

[DOI]

Remote. Sens., 2022

LR-CSNet: Low-Rank Deep Unfolding Network for Image Compressive Sensing.

[BibT_eX]

[DOI]

CoRR, 2022

Input Selection for Bandwidth-Limited Neural Network Inference.

[BibT_eX]

[DOI]

Proceedings of the 2022 SIAM International Conference on Data Mining, 2022

Deep learning based 3D point cloud regression for estimating forest biomass.

[BibT_eX]

[DOI]

Proceedings of the 30th International Conference on Advances in Geographic Information Systems, 2022

2021

Attentional Feature Fusion.

[BibT_eX]

[DOI]

Proceedings of the IEEE Winter Conference on Applications of Computer Vision, 2021

Dataset Sensitive Autotuning of Multi-versioned Code Based on Monotonic Properties - Autotuning in Futhark.

[BibT_eX]

[DOI]

Proceedings of the Trends in Functional Programming - 22nd International Symposium, 2021

Estimating Forest Canopy Height With Multi-Spectral and Multi-Temporal Imagery Using Deep Learning.

[BibT_eX]

[DOI]

Thomas Nyegaard-Signori

Kenneth Grogan

Proceedings of the 2021 IEEE International Conference on Big Data (Big Data), 2021

2020

Implementation of BFASTmonitor Algorithm on Google Earth Engine to Support Large-Area and Sub-Annual Change Monitoring Using Earth Observation Data.

[BibT_eX]

[DOI]

Remote. Sens., 2020

Inferring astrophysical X-ray polarization with deep learning.

[BibT_eX]

[DOI]

CoRR, 2020

Attention as Activation.

[BibT_eX]

[DOI]

Proceedings of the 25th International Conference on Pattern Recognition, 2020

Massively-Parallel Change Detection for Satellite Time Series Data with Missing Values.

[BibT_eX]

[DOI]

Proceedings of the 36th IEEE International Conference on Data Engineering, 2020

Creating cloud-free satellite imagery from image time series with deep learning.

[BibT_eX]

[DOI]

Tzu-Hsin Karen Chen

Alexander V. Prishchepov

Proceedings of the BIGSPATIAL '20: Proceedings of the 9th ACM SIGSPATIAL International Workshop on Analytics for Big Geospatial Data, 2020

Approximate Nearest-Neighbour Fields via Massively-Parallel Propagation-Assisted K-D Trees.

[BibT_eX]

[DOI]

Cosmin Eugen Oancea

Ties Robroek

Proceedings of the 2020 IEEE International Conference on Big Data (IEEE BigData 2020), 2020

2019

Learning Selection Masks for Deep Neural Networks.

[BibT_eX]

[DOI]

CoRR, 2019

Detecting Hardly Visible Roads in Low-Resolution Satellite Time Series Data.

[BibT_eX]

[DOI]

Christoffer Thrysøe

Andreas Borgstad

Martin Brandt

Proceedings of the 2019 IEEE International Conference on Big Data (IEEE BigData), 2019

Magnitude and Uncertainty Pruning Criterion for Neural Networks.

[BibT_eX]

[DOI]

Vinnie Ko

Proceedings of the 2019 IEEE International Conference on Big Data (IEEE BigData), 2019

2018

Artistic movement recognition by consensus of boosted SVM based experts.

[BibT_eX]

[DOI]

Corneliu Florea

J. Vis. Commun. Image Represent., 2018

Bigger Buffer k-d Trees on Multi-Many-Core Systems.

[BibT_eX]

[DOI]

Proceedings of the High Performance Computing for Computational Science - VECPAR 2018, 2018

Massively-parallel break detection for satellite data.

[BibT_eX]

[DOI]

Proceedings of the 30th International Conference on Scientific and Statistical Database Management, 2018

Training Big Random Forests with Little Resources.

[BibT_eX]

[DOI]

Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2018

2017

bufferkdtree: A Python library for massive nearest neighbor queries on multi-many-core devices.

[BibT_eX]

[DOI]

Cosmin E. Oancea

Knowl. Based Syst., 2017

Big Universe, Big Data: Machine Learning and Image Analysis for Astronomy.

[BibT_eX]

[DOI]

Jan Kremer

Kristoffer Stensbo-Smidt

Kim Steenstrup Pedersen

IEEE Intell. Syst., 2017

Artistic Movement Recognition by Boosted Fusion of Color Structure and Topographic Description.

[BibT_eX]

[DOI]

Corneliu Florea

Cosmin Toca

Proceedings of the 2017 IEEE Winter Conference on Applications of Computer Vision, 2017

Deep-learnt classification of light curves.

[BibT_eX]

[DOI]

Proceedings of the 2017 IEEE Symposium Series on Computational Intelligence, 2017

Massively-parallel best subset selection for ordinary least-squares regression.

[BibT_eX]

[DOI]

Proceedings of the 2017 IEEE Symposium Series on Computational Intelligence, 2017

2016

Parallelized rotation and flipping INvariant Kohonen maps (PINK) on GPUs.

[BibT_eX]

[DOI]

Proceedings of the 24th European Symposium on Artificial Neural Networks, 2016

Exploring the spectroscopic diversity of type Ia supernovae with Deep Learning and Unsupervised Clustering.

[BibT_eX]

[DOI]

Arlindo M. M. Trindade

Proceedings of the Astroinformatics 2016, Sorrento, Italy, October 19-25, 2016, 2016

2015

Nearest neighbor density ratio estimation for large-scale applications in astronomy.

[BibT_eX]

[DOI]

Jan Kremer

Kim Steenstrup Pedersen

Astron. Comput., 2015

An Efficient Many-Core Implementation for Semi-Supervised Support Vector Machines.

[BibT_eX]

[DOI]

Proceedings of the Machine Learning, Optimization, and Big Data, 2015

Batch Steepest-Descent-Mildest-Ascent for Interactive Maximum Margin Clustering.

[BibT_eX]

[DOI]

Tapio Pahikkala

Tom Heskes

Proceedings of the Advances in Intelligent Data Analysis XIV, 2015

2014

On Unsupervised Training of Multi-Class Regularized Least-Squares Classifiers.

[BibT_eX]

[DOI]

J. Comput. Sci. Technol., 2014

Fast and simple gradient-based optimization for semi-supervised support vector machines.

[BibT_eX]

[DOI]

Neurocomputing, 2014

A Framework for Data Mining in Wind Power Time Series.

[BibT_eX]

[DOI]

Proceedings of the Data Analytics for Renewable Energy Integration, 2014

Buffer k-d Trees: Processing Massive Nearest Neighbor Queries on GPUs.

[BibT_eX]

[DOI]

Proceedings of the 31th International Conference on Machine Learning, 2014

Speedy greedy feature selection: Better redshift estimation via massive parallelism.

[BibT_eX]

[DOI]

Proceedings of the 22th European Symposium on Artificial Neural Networks, 2014

2013

From Supervised to Unsupervised Support Vector Machines and Applications in Astronomy.

[BibT_eX]

[DOI]

Künstliche Intell., 2013

Wind energy prediction and monitoring with neural computation.

[BibT_eX]

[DOI]

Benjamin Satzger

Neurocomputing, 2013

Learning morphological maps of galaxies with unsupervised regression.

[BibT_eX]

[DOI]

Kai Lars Polsterer

Expert Syst. Appl., 2013

On GPU-Based Nearest Neighbor Queries for Large-Scale Photometric Catalogs in Astronomy.

[BibT_eX]

[DOI]

Proceedings of the KI 2013: Advances in Artificial Intelligence, 2013

Towards Non-linear Constraint Estimation for Expensive Optimization.

[BibT_eX]

[DOI]

Proceedings of the Applications of Evolutionary Computation - 16th European Conference, 2013

Support Vector Machines for Wind Energy Prediction in Smart Grids.

[BibT_eX]

[DOI]

Nils André Treiber

Proceedings of the 27th International Conference on Environmental Informatics for Environmental Protection, 2013

Polynomial Runtime Bounds for Fixed-Rank Unsupervised Least-Squares Classification.

[BibT_eX]

[DOI]

Tapio Pahikkala

Proceedings of the Asian Conference on Machine Learning, 2013

2012

Resilient k-d trees: k-means in space revisited.

[BibT_eX]

[DOI]

Gabriel Moruz

Jan Vahrenhold

Frontiers Comput. Sci., 2012

Efficient recurrent local search strategies for semi- and unsupervised regularized least-squares classification.

[BibT_eX]

[DOI]

Evol. Intell., 2012

Evolutionary kernel density regression.

[BibT_eX]

[DOI]

Expert Syst. Appl., 2012

Sparse Quasi-Newton Optimization for Semi-supervised Support Vector Machines.

[BibT_eX]

Proceedings of the ICPRAM 2012, 2012

Unsupervised Multi-class Regularized Least-Squares Classification.

[BibT_eX]

[DOI]

Proceedings of the 12th IEEE International Conference on Data Mining, 2012

Von überwachten zu unüberwachten Support-Vektor-Maschinen und Anwendungen in der Astronomie.

[BibT_eX]

[DOI]

Proceedings of the Ausgezeichnete Informatikdissertationen 2012, 2012

2011

From supervised to unsupervised support vector machines and applications in astronomy.

[BibT_eX]

[DOI]

PhD thesis, 2011

Short-Term Wind Energy Forecasting Using Support Vector Regression.

[BibT_eX]

[DOI]

Proceedings of the Soft Computing Models in Industrial and Environmental Applications, 2011

Variance Scaling for EDAs Revisited.

[BibT_eX]

[DOI]

Proceedings of the KI 2011: Advances in Artificial Intelligence, 2011

Speedy Local Search for Semi-Supervised Regularized Least-Squares.

[BibT_eX]

[DOI]

Proceedings of the KI 2011: Advances in Artificial Intelligence, 2011

Analysis of wind energy time series with kernel methods and neural networks.

[BibT_eX]

[DOI]

Proceedings of the Seventh International Conference on Natural Computation, 2011

2010

Pruning spanners and constructing well-separated pair decompositions in the presence of memory hierarchies.

[BibT_eX]

[DOI]

Joachim Gudmundsson

Jan Vahrenhold

J. Discrete Algorithms, 2010

Detecting Quasars in Large-Scale Astronomical Surveys.

[BibT_eX]

[DOI]

Proceedings of the Ninth International Conference on Machine Learning and Applications, 2010

Resilient K-d Trees: K-Means in Space Revisited.

[BibT_eX]

[DOI]

Gabriel Moruz

Jan Vahrenhold

Proceedings of the ICDM 2010, 2010

2009

Fast evolutionary maximum margin clustering.

[BibT_eX]

[DOI]

Tapio Pahikkala