43 citations · 126 across the 9 of their papers we have counts for
9 papers
A Conditional Diffusion Model for Electrical Impedance Tomography Image Reconstruction
Shuaikai Shi, Ruiyuan Kang, Panos Liatsis
Electrical impedance tomography (EIT) is a non-invasive imaging technique, capable of reconstructing images of the electrical conductivity of tissues and materials. It is popular i…
Physics-Driven AI Correction in Laser Absorption Sensing Quantification
Ruiyuan Kang, Panos Liatsis, Meixia Geng +1
Laser absorption spectroscopy (LAS) quantification is a popular tool used in measuring temperature and concentration of gases. It has low error tolerance, whereas current ML-based…
Physics-Driven ML-Based Modelling for Correcting Inverse Estimation
Ruiyuan Kang, Tingting Mu, Panos Liatsis +1
When deploying machine learning estimators in science and engineering (SAE) domains, it is critical to avoid failed estimations that can have disastrous consequences, e.g., in aero…
EEE, Remediating the failure of machine learning models via a network-based optimization patch
Ruiyuan Kang, Dimitrios Kyritsis, Panos Liatsis
A network-based optimization approach, EEE, is proposed for the purpose of providing validation-viable state estimations to remediate the failure of pretrained models. To improve o…
k-MS: A novel clustering algorithm based on morphological reconstruction
É. O. Rodrigues, L. Torok, P. Liatsis +2
This work proposes a clusterization algorithm called k-Morphological Sets (k-MS), based on morphological reconstruction and heuristics. k-MS is faster than the CPU-parallel k-Means…
Automated recognition of the pericardium contour on processed CT images using genetic algorithms
E. O. Rodrigues, L. O. Rodrigues, L. S. N. Oliveira +2
This work proposes the use of Genetic Algorithms (GA) in tracing and recognizing the pericardium contour of the human heart using Computed Tomography (CT) images. We assume that ea…