The goal of the project is to study and analyze the most sought-after job profiles related to artificial intelligence on the market, develop education plans for higher education students, conduct education at all partner universities through academic courses with recognition of achieved points, and create a digital academic portal as a gathering place for new […]
News
Fracture Recognition in Paediatric Wrist Radiographs: An Object Detection Approach
Wrist fractures are commonly diagnosed using X-ray imaging, supplemented by magnetic resonance imaging and computed tomography when required. Radiologists can sometimes overlook the fractures because they are difficult to spot. In contrast, some fractures can be easily spotted and only slow down the radiologists because of the reporting systems. We propose a machine learning model […]
Rapid extraction of skin physiological parameters from hyperspectral images using machine learning
Noninvasive assessment of skin structure using hyperspectral images has been intensively studied in recent years. Due to the high computational cost of the classical methods, such as the inverse Monte Carlo (IMC), much research has been done with the aim of using machine learning (ML) methods to reduce the time required for estimating parameters. This […]
Extended Energy-Expenditure Model in Soccer: Evaluating Player Performance in the Context of the Game
Every soccer game influences each player’s performance differently. Many studies have tried to explain the influence of different parameters on the game; however, none went deeper into the core and examined it minute-by-minute. The goal of this study is to use data derived from GPS wearable devices to present a new framework for performance analysis. […]
A Review of Data-Driven Approaches and Techniques for Fault Detection and Diagnosis in HVAC Systems
Heating, ventilation, and air conditioning (HVAC) systems are a popular research topic because buildings’ energy is mostly used for heating and/or cooling. These systems heavily rely on sensory measurements and typically make an integral part of the smart building concept. As such, they require the implementation of fault detection and diagnosis (FDD) methodologies, which should […]
Recognition from the Faculty of Information and Digital Technologies
AIRI center was acknowledged by the Faculty of Informatics and Digital Technologies for successful collaboration in 2020 during the annual meeting of the FIDT.
Block-Adaptive Rényi Entropy-Based Denoising for Non-Stationary Signals
This paper approaches the problem of signal denoising in time-variable noise conditions. Non-stationary noise results in variable degradation of the signal’s useful information content over time. In order to maximize the correct recovery of the useful part of the signal, this paper proposes a denoising method that uses a criterion based on amplitude segmentation and […]
Emphasis on Occupancy Rates in Carbon Emission Comparison for Maritime and Road Passenger Transportation Modes
Carbon emissions generated by the transportation sector represent a large part of total greenhouse gas emissions and are thus subject to various policies and initiatives for emission reduction and the development of sustainable transportation networks. Furthermore, passenger transportation generates a significant amount of emissions within this sector, especially in those countries with large and developed […]
