Machine Learning Laboratory deals with numerous challenges in several fields, by developing and integrating suitable data-driven machine learning solutions to perceived problems.
Head of Laboratory
Laboratory Projects
Machine Learning for Knowledge Transfer in Medical Radiology
European Network for assuring food integrity using non-destructive spectral sensors
National Competence Centres in the Framework of EuroHPC (EUROCC)
Hyperspectral Image Analysis Using Machine Learning and Adaptive Data-Driven Filtering
Development of machine-learning-based techniques for illness and injury detection in medical images
Computer-Aided Digital Analysis And Classification of Signals
A Network for Gravitational Waves, Geophysics and Machine Learning
Image Processing, Information Engineering & Interdisciplinary Knowledge Exchange
Laboratory Research Papers
The Choice of Time–Frequency Representations of Non-Stationary Signals Affects Machine Learning Model Accuracy: A Case Study on Earthquake Detection from LEN-DB Data
Intra-domain and cross-domain transfer learning for time series data—How transferable are the features?
Transfer learning: Improving neural network based prediction of earthquake ground shaking for an area with insufficient training data
Cast suppression in radiographs by generative adversarial networks
Deep Semi-Supervised Algorithm for Learning Cluster-Oriented Representations of Medical Images Using Partially Observable DICOM Tags and Images
XAOM: A method for automatic alignment and orientation of radiographs for computer-aided medical diagnosis
Deep Learning for Feature Extraction in Remote Sensing: A Case-Study of Aerial Scene Classification
Rapid prediction of earthquake ground shaking intensity using raw waveform data and a convolutional neural network
Automatic Annotation of Narrative Radiology Reports
Adaptive Filtering and Analysis of EEG Signals in the Time-Frequency Domain Based on the Local Entropy
Automatic Music Transcription for Traditional Woodwind Instruments Sopele
Local-Entropy Based Approach for X-Ray Image Segmentation and Fracture Detection
Adaptive State Estimator With Intersection of Confidence Intervals Based Preprocessing
Mirroring Quasi-Symmetric Organ Observations for Reducing Problem Complexity
Semi-automated detection of anterior cruciate ligament injury from MRI
Uncensoring censored data for machine learning: A likelihood-based approach
Learning Bayesian networks from survival data using weighting censored instances
Impact of censoring on learning Bayesian networks in survival modelling
Affiliated Researchers
- Jonatan Lerga, Assist. Prof., PhD (RITEH)
- Arian Skoki, mag. ing. comp. (RITEH)
- Dejan Ljubobratović
- Franko Hržić, mag. ing. comp. (RITEH)
- Iva Matetić
- Ivan Štajduhar, Assoc. Prof., PhD (RITEH)
- Marko Gulić, Assist. Prof., PhD (PFRI)
- Mateja Napravnik, mag. ing. comp.
- Marko Njirjak, mag. ing. comp.
- Teo Manojlović, mag. ing. comp.
