Main Track: Optimization of Image Acquisition for Earth Observation Satellites via Quantum Computing
Complexity-driven sampling for Bagging
A pseudo-label guided hybrid approach for unsupervised domain adaptation⁾́p6
Combining of Markov Random Field and Convolutional Neural Networks for Hyper/Multispectral Image Classification
Plant Disease Detection and Classification using a Deep learning-based framework
Evaluating Text Classification in the Legal Domain Using BERT Embeddings
Rapid and Low-Cost Evaluation of Multi-Fidelity Scheduling Algorithms for Hyperparameter Optimization
The Applicability of Federated Learning to Official Statistics
Generating Wildfire Heat Maps with Twitter and BERT
An urban simulator integrated with a genetic algorithm for efficient traffic light coordination
GPU-Based Acceleration of the Rao Optimization Algorithms: Application to the Solution of Large Systems of Nonlinear Equations
Direct determination of Operational Value-at-Risk using Descriptive Statistics
Using Deep Learning models to Predict the Electrical Conductivity of the influent in a Wastewater Treatment Plant. -Unsupervised Defect Detection for Infrastructure Inspection
Generating Adversarial Examples using LAD
Emotion extraction from Likert-Scale questionnaires ⁰́b3 an additional dimension to Psychology Instruments
Recent applications of pre-aggregation functions
A Probabilistic Approach: Querying Web Resources In The Presence Of Uncertainty
Domain Adaptation in Transformer models: Question Answering of Dutch Government Policies
Sustainable On-Street Parking Mapping with Deep Learning and Airborne Imagery
Hebbian Learning-Guided Random Walks for Enhanced Community Detection in Correlation-Based Brain Networks
Hebbian Learning-Guided Random Walks for Enhanced Community Detection in Correlation-Based Brain Networks
Language Models for Automatic Distribution of Review Notes in Movie Production
Extracting Knowledge from Incompletely Known Models
Threshold-based Classification to Enhance Confidence in Open Set of Legal Texts
Comparing ranking learning algorithms for information retrieval systems
Analyzing the influence of market event correction for forecasting stock prices using Recurrent Neural Networks
Measuring the relationship between the use of typical Manosphere discourse and the engagement of a user with the pick-up artist community⁾́p6
Uniform Design of Experiments for Equality Constraints
Globular Cluster Detection in M33 Using Multiple Views Representation Learning
Segmentation of Brachial Plexus Ultrasound Images Based on Modified SegNet Model
Unsupervised Online Event Ranking for IT Operations⁾́p6
A Subgraph Embedded GIN with Attention for Graph Classification
A Machine Learning Approach to Predict Cyclists⁰́b9 Functional Threshold Power
Combining Regular Expressions and Supervised Algorithms for Clinical Text Classification
MODELING THE INK TUNING PROCESS USING MACHINE LEARNING
Depth and Width Adaption of DNN for Data Stream Classification with Concept Drifts*
FETCH: A Memory-Efficient Replay Approach for Continual Learning in Image Classification
Enhanced SVM-SMOTE with Cluster Consistency for Imbalanced Data Classification
Preliminary Study on Unexploded Ordnance Classification in Underwater Environment Based on the Raw Magnetometry Data.
Efficient Model For Probabilistic Web resources under uncertainty
Unlocking the Black Box: Towards Interactive Explainable Automated Machine Learning
Machine Learning for Time Series Forecasting Using State Space Models
Causal graph discovery for explainable insights on marine biotoxin shellfish contamination
Special Session on Federated Learning and (pre) Aggregation in Machine Learning: Adaptative fuzzy measure for edge detection
Special Session on Intelligent Techniques for Real-world Applications of Renewable Energy and Green Transport: Prediction and Uncertainty Estimation in Power Curves of Wind Turbines Using -SVR
Glide Ratio Optimization for Wind Turbine Airfoils based on Genetic Algorithms
Special Session on Data Selection in Machine Learning: Detecting Image Forgery Using Support Vector Machine and Texture Features
Instance selection techniques for large volumes of data.