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
Transversal Skills in Applied Artificial Intelligence (TSAAI)
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
Fracture Recognition in Paediatric Wrist Radiographs: An Object Detection Approach
Rapid extraction of skin physiological parameters from hyperspectral images using machine learning
Extended Energy-Expenditure Model in Soccer: Evaluating Player Performance in the Context of the Game
A Review of Data-Driven Approaches and Techniques for Fault Detection and Diagnosis in HVAC Systems
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, 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.
