Search
Search Results
-
-
Metadata Improves Segmentation Through Multitasking Elicitation
Metainformation is a common companion to biomedical images. However, this potentially powerful additional source of signal from image acquisition has...
-
Black-Box Unsupervised Domain Adaptation for Medical Image Segmentation
Unsupervised Domain Adaptation (UDA) is one of the key technologies to solve the problem of obtaining ground truth labels needed for supervised...
-
A Taxonomy for Platform Revenue Models: An Empirical-to-Conceptual Development Approach
In the field of Information Systems and Software Engineering, taxonomies are widely employed to organize and present well-designed knowledge. They...
-
Progressing from Process Mining Insights to Process Improvement: Challenges and Recommendations
Many organizations have adopted process mining to analyze their business processes, gain insights into their performance, and identify improvement...
-
Hierarchical Compositionality in Hyperbolic Space for Robust Medical Image Segmentation
Deep learning based medical image segmentation models need to be robust to domain shifts and image distortion for the safe translation of these...
-
Compositional Representation Learning for Brain Tumour Segmentation
For brain tumour segmentation, deep learning models can achieve human expert-level performance given a large amount of data and pixel-level...
-
A Model-Driven Approach to SAP S/4HANA Development
While Enterprise Resource Planning systems such as SAP S/4HANA play a key role for many companies, they rarely come alone but are connected to other...
-
Rectify Sensor Data in IoT: A Case Study on Enabling Process Mining for Logistic Process in an Air Cargo Terminal
The Internet of Things (IoT) has empowered enterprises to optimize process efficiency and productivity by analyzing sensor data. This can be achieved...
-
Towards Scaling External Feedback for Early-Stage Researchers: A Survey Study
Feedback on research artefacts from people beyond local research groups, such as researchers in online research communities, has the potential to...
-
Double Deep Q-Network-Based Time and Energy-Efficient Mobility-Aware Workflow Migration Approach
With the emergence of the Fog paradigm, the relocation of computational capabilities to the network’s edge has become imperative to support the...
-
Feature Selection and Classification for Searching Light at Night Exposure and Students’ Weight Relationship
Circadian rhythm is essential for living beings. This rhythm regulates slee** and waking patterns, hormone production, eating habits, digestion,...
-
Boosting Kidney Stone Identification in Endoscopic Images Using Two-Step Transfer Learning
Knowing the cause of kidney stone formation is crucial to establish treatments that prevent recurrence. There are currently different approaches for...
-
Learning Neural Radiance Fields of Forest Structure for Scalable and Fine Monitoring
This work leverages neural radiance fields and remote sensing for forestry applications. Here, we show neural radiance fields offer a wide range of...
-
Large Sentiment Dictionary of Russian Words
Sentiment analysis is a widely studied area of computational linguistics. The main tool for sentiment analysis of texts are dictionaries with...
-
Nonlinear DIP-DiracVTV Model for Color Image Restoration
Variational models for inverse problems are mainly based on the choice of the regularizer, whose goal is to give the solutions some desirable...
-
Load Demand Forecasting Using a Long-Short Term Memory Neural Network
Electric power load forecasting is very important for the operation and the planning of a utility company. Decisions of the electric market, electric...
-
Bayesian Network-Based Multi-objective Estimation of Distribution Algorithm for Feature Selection Tailored to Regression Problems
Feature selection is an essential pre-processing step in Machine Learning for improving the performance of models, reducing the time of predictions,...
-
Semi-supervised Learning of Non-stationary Acoustic Signals Using Time-Frequency Energy Maps
Non-stationary signals are time-varying signals that represent various real-world phenomena, such as biomedical signals, vibrating machinery, and...
-
Hand Gesture Recognition Applied to the Interaction with Video Games
In this work, a hand gesture recognition system was created for 11 different gestures. The system employed CNN-LSTM artificial neural networks and...