Search Results - "Gawlikowski, Jakob"

A survey of uncertainty in deep neural networks by Gawlikowski, Jakob, Tassi, Cedrique Rovile Njieutcheu, Ali, Mohsin, Lee, Jongseok, Humt, Matthias, Feng, Jianxiang, Kruspe, Anna, Triebel, Rudolph, Jung, Peter, Roscher, Ribana, Shahzad, Muhammad, Yang, Wen, Bamler, Richard, Zhu, Xiao Xiang

“…Over the last decade, neural networks have reached almost every field of science and become a crucial part of various real world applications. Due to the…”
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Handling unexpected inputs: incorporating source-wise out-of-distribution detection into SAR-optical data fusion for scene classification by Gawlikowski, Jakob, Saha, Sudipan, Niebling, Julia, Zhu, Xiao Xiang

“…The fusion of synthetic aperture radar (SAR) and optical satellite data is widely used for deep learning based scene classification. Counter-intuitively such…”
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Explaining the Effects of Clouds on Remote Sensing Scene Classification by Gawlikowski, Jakob, Ebel, Patrick, Schmitt, Michael, Zhu, Xiao Xiang

“…Most of Earth is covered by haze or clouds, impeding the constant monitoring of our planet. Preceding works have documented the detrimental effects of cloud…”
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Few-shot learning for skin lesion classification: A prototypical networks approach by Chamarthi, Sireesha, Fogelberg, Katharina, Gawlikowski, Jakob, Brinker, Titus J.

“…Prototypical networks (PN) have emerged as one of multiple effective approaches for few-shot learning (FSL), even in medical image classification. This study…”
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An Advanced Dirichlet Prior Network for Out-of-Distribution Detection in Remote Sensing by Gawlikowski, Jakob, Saha, Sudipan, Kruspe, Anna, Zhu, Xiao Xiang

“…Remote sensing deals with a plethora of sensors, a large number of classes/categories, and a huge variation in geography. Due to the difficulty of collecting…”
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Leveraging Graph and Deep Learning Uncertainties to Detect Anomalous Maritime Trajectories by Singh, Sandeep Kumar, Fowdur, Jaya Shradha, Gawlikowski, Jakob, Medina, Daniel

“…Understanding and representing traffic patterns are key to detecting anomalous trajectories in the transportation domain. However, some trajectories can…”
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FUSING MULTIPLE UNTRAINED NETWORKS FOR HYPERSPECTRAL CHANGE DETECTION by Saha, S., Gawlikowski, J., Zhu, X. X.

“…Change detection in hyperspectral images is challenging due to the presence of a large number of spectral bands. Due to the differences in band composition, a…”
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Estimating Uncertainty of Deep Learning Multi-Label Classifications Using Laplace Approximation by Rewicki, Ferdinand, Gawlikowski, Jakob

“…Deep learning methods have become valuable tools in remote sensing for tasks like aerial scene classification or land cover analysis. Dealing with noisy and…”
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The Unreasonable Effectiveness of Deep Evidential Regression by Meinert, Nis, Gawlikowski, Jakob, Lavin, Alexander

“…AAAI, vol. 37, no. 8, pp. 9134-9142, Jun. 2023 There is a significant need for principled uncertainty reasoning in machine learning systems as they are…”
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Exploiting Text-Image Latent Spaces for the Description of Visual Concepts by Schmalwasser, Laines, Gawlikowski, Jakob, Denzler, Joachim, Niebling, Julia

“…Concept Activation Vectors (CAVs) offer insights into neural network decision-making by linking human friendly concepts to the model's internal feature…”
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Unraveling Anomalies in Time: Unsupervised Discovery and Isolation of Anomalous Behavior in Bio-regenerative Life Support System Telemetry by Rewicki, Ferdinand, Gawlikowski, Jakob, Niebling, Julia, Denzler, Joachim

“…Lecture Notes in Computer Science, vol. 14949 (2024) 207-222 The detection of abnormal or critical system states is essential in condition monitoring. While…”
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On the Fusion Strategies of Sentinel-1 and Sentinel-2 Data for Local Climate Zone Classification by Gawlikowski, Jakob, Schmitt, Michael, Kruspe, Anna, Zhu, Xiao Xiang

“…Local Climate Zone (LCZ) classification is the most commonly used scheme to analyze how local urban morphology affects the climate of local areas…”
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Lightning UQ Box: A Comprehensive Framework for Uncertainty Quantification in Deep Learning by Lehmann, Nils, Gawlikowski, Jakob, Stewart, Adam J, Jancauskas, Vytautas, Depeweg, Stefan, Nalisnick, Eric, Gottschling, Nina Maria

“…Uncertainty quantification (UQ) is an essential tool for applying deep neural networks (DNNs) to real world tasks, as it attaches a degree of confidence to DNN…”
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Robust Distribution-Shift Aware Sar-Optical data Fusion for Multi-Label Scene Classification by Gawlikowski, Jakob, Saha, Sudipan, Niebling, Julia, Zhu, Xiao Xiang

“…Out-of-distribution (OOD) detection is an emerging research topic in remote sensing where existing works focus on single sensor analysis. However, many remote…”
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Towards Out-of-Distribution Detection for Remote Sensing by Gawlikowski, Jakob, Saha, Sudipan, Kruspe, Anna, Zhu, Xiao Xiang

“…In remote sensing, distributional mismatch between the training and test data may arise due to several reasons, including unseen classes in the test data,…”
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Compact Feature Representation for Unsupervised Ood Detection by Saha, Sudipan, Gawlikowski, Jakob, Nandy, Jay, Zhu, Xiao Xiang

“…Distributional mismatch between training and test data may cause the remote sensing models to behave in unpredictable manner, thus reducing the trustworthiness…”
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Leveraging Graph and Deep Learning Uncertainties to Detect Anomalous Trajectories by Singh, Sandeep Kumar, Fowdur, Jaya Shradha, Gawlikowski, Jakob, Medina, Daniel

“…Understanding and representing traffic patterns are key to detecting anomalous trajectories in the transportation domain. However, some trajectories can…”
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Out-of-distribution detection in satellite image classification by Gawlikowski, Jakob, Saha, Sudipan, Kruspe, Anna, Zhu, Xiao Xiang

“…In satellite image analysis, distributional mismatch between the training and test data may arise due to several reasons, including unseen classes in the test…”
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A Survey of Uncertainty in Deep Neural Networks by Gawlikowski, Jakob, Tassi, Cedrique Rovile Njieutcheu, Ali, Mohsin, Lee, Jongseok, Humt, Matthias, Feng, Jianxiang, Kruspe, Anna, Triebel, Rudolph, Jung, Peter, Roscher, Ribana, Shahzad, Muhammad, Yang, Wen, Bamler, Richard, Zhu, Xiao Xiang

“…Due to their increasing spread, confidence in neural network predictions became more and more important. However, basic neural networks do not deliver…”
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