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09/12/2023
Active Label Refinement for Semantic Segmentation of Satellite Images
Remote sensing through semantic segmentation of satellite images contrib...
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08/14/2023
Active Bird2Vec: Towards End-to-End Bird Sound Monitoring with Transformers
We propose a shift towards end-to-end learning in bird sound monitoring ...
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08/02/2023
Height Change Feature Based Free Space Detection
In the context of autonomous forklifts, ensuring non-collision during tr...
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07/26/2023
Unraveling the Complexity of Splitting Sequential Data: Tackling Challenges in Video and Time Series Analysis
Splitting of sequential data, such as videos and time series, is an esse...
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07/12/2023
Smart Infrastructure: A Research Junction
Complex inner-city junctions are among the most critical traffic areas f...
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07/12/2023
The IMPTC Dataset: An Infrastructural Multi-Person Trajectory and Context Dataset
Inner-city intersections are among the most critical traffic areas for i...
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07/10/2023
DADO – Low-Cost Selection Strategies for Deep Active Design Optimization
In this experience report, we apply deep active learning to the field of...
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06/16/2023
ActiveGLAE: A Benchmark for Deep Active Learning with Transformers
Deep active learning (DAL) seeks to reduce annotation costs by enabling ...
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05/24/2023
Sampling-based Uncertainty Estimation for an Instance Segmentation Network
The examination of uncertainty in the predictions of machine learning (M...
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05/09/2023
Dataset of a parameterized U-bend flow for Deep Learning Applications
This dataset contains 10,000 fluid flow and heat transfer simulations in...
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04/29/2023
Sensor Equivariance by LiDAR Projection Images
In this work, we propose an extension of conventional image data by an a...
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04/05/2023
Multi-annotator Deep Learning: A Probabilistic Framework for Classification
Solving complex classification tasks using deep neural networks typicall...
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10/17/2022
Space, Time, and Interaction: A Taxonomy of Corner Cases in Trajectory Datasets for Automated Driving
Trajectory data analysis is an essential component for highly automated ...
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10/12/2022
Fast Bayesian Updates for Deep Learning with a Use Case in Active Learning
Retraining deep neural networks when new data arrives is typically compu...
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10/06/2022
A Review of Uncertainty Calibration in Pretrained Object Detectors
In the field of deep learning based computer vision, the development of ...
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04/29/2022
Task Embedding Temporal Convolution Networks for Transfer Learning Problems in Renewable Power Time-Series Forecast
Task embeddings in multi-layer perceptrons for multi-task learning and i...
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04/28/2022
Model Selection, Adaptation, and Combination for Deep Transfer Learning through Neural Networks in Renewable Energies
There is recent interest in using model hubs, a collection of pre-traine...
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04/01/2022
Synthetic Photovoltaic and Wind Power Forecasting Data
Photovoltaic and wind power forecasts in power systems with a high share...
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02/14/2022
Design of Explainability Module with Experts in the Loop for Visualization and Dynamic Adjustment of Continual Learning
Continual learning can enable neural networks to evolve by learning new ...
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09/23/2021
A Survey on Cost Types, Interaction Schemes, and Annotator Performance Models in Selection Algorithms for Active Learning in Classification
Pool-based active learning (AL) aims to optimize the annotation process ...
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09/20/2021
Description of Corner Cases in Automated Driving: Goals and Challenges
Scaling the distribution of automated vehicles requires handling various...
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08/31/2021
Toward AI-enhanced online-characterization and shaping of ultrashort X-ray free-electron laser pulses
X-ray free-electron lasers (XFELs) as the world`s most brilliant light s...
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08/09/2021
Probabilistic Active Learning for Active Class Selection
In machine learning, active class selection (ACS) algorithms aim to acti...
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06/30/2021
Cyclist Trajectory Forecasts by Incorporation of Multi-View Video Information
This article presents a novel approach to incorporate visual cues from v...
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06/04/2021
Pose and Semantic Map Based Probabilistic Forecast of Vulnerable Road Users' Trajectories
In this article, an approach for probabilistic trajectory forecasting of...
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05/14/2021
Towards Sensor Data Abstraction of Autonomous Vehicle Perception Systems
Full-stack autonomous driving perception modules usually consist of data...
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05/04/2021
Out-of-distribution Detection and Generation using Soft Brownian Offset Sampling and Autoencoders
Deep neural networks often suffer from overconfidence which can be partl...
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04/19/2021
Cyclist Intention Detection: A Probabilistic Approach
This article presents a holistic approach for probabilistic cyclist inte...
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03/05/2021
An Application-Driven Conceptualization of Corner Cases for Perception in Highly Automated Driving
Systems and functions that rely on machine learning (ML) are the basis o...
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01/04/2021
CLeaR: An Adaptive Continual Learning Framework for Regression Tasks
Catastrophic forgetting means that a trained neural network model gradua...
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09/29/2020
Quantile Surfaces – Generalizing Quantile Regression to Multivariate Targets
In this article, we present a novel approach to multivariate probabilist...
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09/29/2020
Efficient SVDD Sampling with Approximation Guarantees for the Decision Boundary
Support Vector Data Description (SVDD) is a popular one-class classifier...
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06/09/2020
Off-the-shelf sensor vs. experimental radar – How much resolution is necessary in automotive radar classification?
Radar-based road user detection is an important topic in the context of ...
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06/02/2020
Toward Optimal Probabilistic Active Learning Using a Bayesian Approach
Gathering labeled data to train well-performing machine learning models ...
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04/29/2020
Emerging Relation Network and Task Embedding for Multi-Task Regression Problems
Multi-task learning (mtl) provides state-of-the-art results in many appl...
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04/29/2020
Extended Coopetitive Soft Gating Ensemble
This article is about an extension of a recent ensemble method called Co...
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02/07/2020
Trust Your Model: Iterative Label Improvement and Robust Training by Confidence Based Filtering and Dataset Partitioning
State-of-the-art, high capacity deep neural networks not only require la...
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12/13/2019
Seeing Around Street Corners: Non-Line-of-Sight Detection and Tracking In-the-Wild Using Doppler Radar
Conventional sensor systems record information about directly visible ob...
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07/08/2019
A Multi-Stage Clustering Framework for Automotive Radar Data
Radar sensors provide a unique method for executing environmental percep...
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06/03/2019
Generative Adversarial Networks for Operational Scenario Planning of Renewable Energy Farms: A Study on Wind and Photovoltaic
For the integration of renewable energy sources, power grid operators ne...
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05/31/2019
Influences in Forecast Errors for Wind and Photovoltaic Power: A Study on Machine Learning Models
Despite the increasing importance of forecasts of renewable energy, curr...
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05/28/2019
Radar-based Road User Classification and Novelty Detection with Recurrent Neural Network Ensembles
Radar-based road user classification is an important yet still challengi...
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05/28/2019
Automated Ground Truth Estimation For Automotive Radar Tracking Applications With Portable GNSS And IMU Devices
Baseline generation for tracking applications is a difficult task when w...
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05/27/2019
Radar-based Feature Design and Multiclass Classification for Road User Recognition
The classification of individual traffic participants is a complex task,...
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05/27/2019
Automated Ground Truth Estimation of Vulnerable Road Users in Automotive Radar Data Using GNSS
Annotating automotive radar data is a difficult task. This article prese...
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05/16/2019
Collaborative Interactive Learning -- A clarification of terms and a differentiation from other research fields
The field of collaborative interactive learning (CIL) aims at developing...
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01/29/2019
Limitations of Assessing Active Learning Performance at Runtime
Classification algorithms aim to predict an unknown label (e.g., a quali...
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09/11/2018
Detecting Intentions of Vulnerable Road Users Based on Collective Intelligence
Vulnerable road users (VRUs, i.e. cyclists and pedestrians) will play an...
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08/14/2018
Quantifying the Influences on Probabilistic Wind Power Forecasts
In recent years, probabilistic forecasts techniques were proposed in res...
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08/08/2018