research
∙
09/12/2023
Active Label Refinement for Semantic Segmentation of Satellite Images
Remote sensing through semantic segmentation of satellite images contrib...
share
research
∙
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 ...
research
∙
08/02/2023
Height Change Feature Based Free Space Detection
In the context of autonomous forklifts, ensuring non-collision during tr...
research
∙
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...
research
∙
07/12/2023
Smart Infrastructure: A Research Junction
Complex inner-city junctions are among the most critical traffic areas f...
research
∙
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...
research
∙
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...
research
∙
06/16/2023
ActiveGLAE: A Benchmark for Deep Active Learning with Transformers
Deep active learning (DAL) seeks to reduce annotation costs by enabling ...
research
∙
05/24/2023
Sampling-based Uncertainty Estimation for an Instance Segmentation Network
The examination of uncertainty in the predictions of machine learning (M...
research
∙
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...
research
∙
04/29/2023
Sensor Equivariance by LiDAR Projection Images
In this work, we propose an extension of conventional image data by an a...
research
∙
04/05/2023
Multi-annotator Deep Learning: A Probabilistic Framework for Classification
Solving complex classification tasks using deep neural networks typicall...
research
∙
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 ...
research
∙
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...
research
∙
10/06/2022
A Review of Uncertainty Calibration in Pretrained Object Detectors
In the field of deep learning based computer vision, the development of ...
research
∙
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...
research
∙
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...
research
∙
04/01/2022
Synthetic Photovoltaic and Wind Power Forecasting Data
Photovoltaic and wind power forecasts in power systems with a high share...
research
∙
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 ...
research
∙
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 ...
research
∙
09/20/2021
Description of Corner Cases in Automated Driving: Goals and Challenges
Scaling the distribution of automated vehicles requires handling various...
research
∙
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...
research
∙
08/09/2021
Probabilistic Active Learning for Active Class Selection
In machine learning, active class selection (ACS) algorithms aim to acti...
research
∙
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...
research
∙
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...
research
∙
05/14/2021
Towards Sensor Data Abstraction of Autonomous Vehicle Perception Systems
Full-stack autonomous driving perception modules usually consist of data...
research
∙
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...
research
∙
04/19/2021
Cyclist Intention Detection: A Probabilistic Approach
This article presents a holistic approach for probabilistic cyclist inte...
research
∙
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...
research
∙
01/04/2021
CLeaR: An Adaptive Continual Learning Framework for Regression Tasks
Catastrophic forgetting means that a trained neural network model gradua...
research
∙
09/29/2020
Quantile Surfaces – Generalizing Quantile Regression to Multivariate Targets
In this article, we present a novel approach to multivariate probabilist...
research
∙
09/29/2020
Efficient SVDD Sampling with Approximation Guarantees for the Decision Boundary
Support Vector Data Description (SVDD) is a popular one-class classifier...
research
∙
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 ...
research
∙
06/02/2020
Toward Optimal Probabilistic Active Learning Using a Bayesian Approach
Gathering labeled data to train well-performing machine learning models ...
research
∙
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...
research
∙
04/29/2020
Extended Coopetitive Soft Gating Ensemble
This article is about an extension of a recent ensemble method called Co...
research
∙
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...
research
∙
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...
research
∙
07/08/2019
A Multi-Stage Clustering Framework for Automotive Radar Data
Radar sensors provide a unique method for executing environmental percep...
research
∙
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...
research
∙
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...
research
∙
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...
research
∙
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...
research
∙
05/27/2019
Radar-based Feature Design and Multiclass Classification for Road User Recognition
The classification of individual traffic participants is a complex task,...
research
∙
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...
research
∙
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...
research
∙
01/29/2019
Limitations of Assessing Active Learning Performance at Runtime
Classification algorithms aim to predict an unknown label (e.g., a quali...
research
∙
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...
research
∙
08/14/2018
Quantifying the Influences on Probabilistic Wind Power Forecasts
In recent years, probabilistic forecasts techniques were proposed in res...
research
∙
08/08/2018
