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检索条件"机构=Machine Learning and Data Analytics Group"
52 条 记 录,以下是21-30 订阅
排序:
Estimating the robustness of classification models by the structure of the learned feature-space
arXiv
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arXiv 2021年
作者: Ho, Kalun Pfreundt, Franz-Josef Keuper, Janis Keuper, Margret CC-HPC Fraunhofer ITWM Fraunhofer-Platz 1 Kaiserslautern67663 Germany Institute for Machine Learning and Analytics Offenburg University Germany Data and Web Science Group University of Mannheim Germany
Over the last decade, the development of deep image classification networks has mostly been driven by the search for the best performance in terms of classification accuracy on standardized benchmarks like ImageNet. M... 详细信息
来源: 评论
learning Embeddings for Image Clustering: An Empirical Study of Triplet Loss Approaches
Learning Embeddings for Image Clustering: An Empirical Study...
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International Conference on Pattern Recognition
作者: Kalun Ho Janis Keuper Franz-Josef Pfreundt Margret Keuper Data and Web Science Group University of Mannheim Germany Institute for Machine Learning and Analytics (IMLA) Offenburg University Germany Competence Center High Performance Computing Fraunhofer ITWM Kaiserslautern Germany
In this work, we evaluate two different image clustering objectives, k-means clustering and correlation clustering, in the context of Triplet Loss induced feature space embeddings. Specifically, we train a convolution... 详细信息
来源: 评论
XPASC: Measuring Generalization in Weak Supervision by Explainability and Association
arXiv
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arXiv 2022年
作者: März, Luisa Asgari, Ehsaneddin Braune, Fabienne Zimmermann, Franziska Roth, Benjamin Research Group Data Mining and Machine Learning Faculty of Computer Science University of Vienna Vienna Austria Faculty of Philological and Cultural Studies University of Vienna Vienna Austria AI Innovation & Pre-Development Data:Lab Volkswagen AG Munich Germany UniVie Docotoral School Computer Science Vienna Austria CAPE Analytics Mountain ViewCA United States
Weak supervision is leveraged in a wide range of domains and tasks due to its ability to create massive amounts of labeled data, requiring only little manual effort. Standard approaches use labeling functions to speci...
来源: 评论
Predicting Influential Higher-Order Patterns in Temporal Network data
arXiv
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arXiv 2021年
作者: Gote, Christoph Perri, Vincenzo Scholtes, Ingo Data Analytics Group University of Zurich Zurich Switzerland Chair of Systems Design ETH Zurich Zurich Switzerland Chair of Machine Learning for Complex Networks University of Würzburg Würzburg Germany
Networks are frequently used to model complex systems comprised of interacting elements. While edges capture the topology of direct interactions, the true complexity of many systems originates from higher-order patter... 详细信息
来源: 评论
Deep learning Based Prediction of Sun-Induced Fluorescence from Hyplant Imagery
Deep Learning Based Prediction of Sun-Induced Fluorescence f...
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IEEE International Symposium on Geoscience and Remote Sensing (IGARSS)
作者: Jim Buffat Miguel Pato Kevin Alonso Stefan Auer Emiliano Carmona Stefan Maier Rupert Müller Patrick Rademske Uwe Rascher Hanno Scharr Forschungszentrum Jülich GmbH Institute of Bio- and Geosciences IBG-2: Plant Sciences Jülich Germany German Aerospace Center (DLR) Earth Observation Center Remote Sensing Technology Institute Oberpfaffenhofen Germany RHEA Group c/o European Space Agency (ESA) Frascati Italy Forschungszentrum Jülich GmbH Institute of Advanced Simulations IAS-8: Data Analytics and Machine Learning Jülich Germany
The retrieval of sun-induced fluorescence (SIF) from hyper-spectral imagery is an ill-posed problem that has been tackled in different ways. We present a novel retrieval method combining semi-supervised deep learning ...
来源: 评论
Fast machine learning Simulator of At-Sensor Radiances for Solar-Induced Fluorescence Retrieval with DESIS and Hyplant
Fast Machine Learning Simulator of At-Sensor Radiances for S...
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IEEE International Symposium on Geoscience and Remote Sensing (IGARSS)
作者: Miguel Pato Kevin Alonso Stefan Auer Jim Buffat Emiliano Carmona Stefan Maier Rupert Müller Patrick Rademske Uwe Rascher Hanno Scharr Earth Observation Center Remote Sensing Technology Institute German Aerospace Center (DLR) Germany Largo Galileo Galilei RHEA Group c/o European Space Agency (ESA) Frascati Italy Institute of Bio- and Geosciences IBG-2: Plant Sciences Forschungszentrum Jülich GmbH Julich Germany Institute of Advanced Simulations IAS-8: Data Analytics and Machine Learning Forschungszentrum Jülich GmbH Jülich Germany
In many remote sensing applications the measured radiance needs to be corrected for atmospheric effects to study surface properties such as reflectance, temperature or emission features. The correction often applies r...
来源: 评论
Hierarchical Bayesian approach for adaptive integration of Bragg peaks in time-of-flight neutron scattering data
arXiv
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arXiv 2024年
作者: Reshniak, Viktor Wang, Xiaoping Zhang, Guannan Liu, Siyan Yin, Junqi Data Analysis and Machine Learning Group Oak Ridge National Laboratory 1 Bethel Valley Rd Oak RidgeTN37830 United States Single Crystal Diffraction Oak Ridge National Laboratory 1 Bethel Valley Rd Oak RidgeTN37830 United States Computational Earth Sciences Group Oak Ridge National Laboratory 1 Bethel Valley Rd Oak RidgeTN37830 United States Analytics and AI Methods at Scale Oak Ridge National Laboratory 1 Bethel Valley Rd Oak RidgeTN37830 United States
The Spallation Neutron Source (SNS) at Oak Ridge National Laboratory (ORNL) operates in the event mode. Time-of-flight (TOF) information about each detected neutron is collected separately and saved as a descriptive e... 详细信息
来源: 评论
Big data = Big Insights? Operationalising Brooks’ Law in a Massive GitHub data Set
arXiv
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arXiv 2022年
作者: Gote, Christoph Schweitzer, Frank Mavrodiev, Pavlin Scholtes, Ingo Department of Systems Design ETH Zurich Weinbergstrasse 56/58 Zurich8092 Switzerland Department of Computer Science XV - Machine Learning for Complex Networks Julius-Maximilians-Universität Würzburg Friedrich-Bergius-Ring 30 Würzburg97076 Germany Data Analytics Group University of Zurich Binzmühlestrasse 14 Zurich8050 Switzerland
Massive data from software repositories and collaboration tools are widely used to study social aspects in software development. One question that several recent works have addressed is how a software project’s size ... 详细信息
来源: 评论
Latent space conditioning on generative adversarial networks
arXiv
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arXiv 2020年
作者: Lopez, Ricard Durall Ho, Kalun Pfreundt, Franz-Josef Keuper, Janis Fraunhofer ITWM Germany IWR University of Heidelberg Germany Fraunhofer Center Machine Learning Germany Data and Web Science Group University of Mannheim Germany Institute for Machine Learning and Analytics Offenburg University Germany
Generative adversarial networks are the state of the art approach towards learned synthetic image generation. Although early successes were mostly unsupervised, bit by bit, this trend has been superseded by approaches... 详细信息
来源: 评论
Watch your Up-Convolution: CNN Based Generative Deep Neural Networks are Failing to Reproduce Spectral Distributions
arXiv
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arXiv 2020年
作者: Durall, Ricard Keuper, Margret Keuper, Janis Competence Center High Performance Computing Fraunhofer ITWM Kaiserslautern Germany Data- and Webscience Group University Mannheim Germany IWR University of Heidelberg Germany Institute for Machine Learning and Analytics Offenburg University Germany
Generative convolutional deep neural networks, e.g. popular GAN architectures, are relying on convolution based up-sampling methods to produce non-scalar outputs like images or video sequences. In this paper, we show ... 详细信息
来源: 评论