73 citations · 249 across the 20 of their papers we have counts for
21 papers
ROI Extraction in Thermographic Breast Images Using Genetic Algorithms
LC Mendes, EO Rodrigues, Sandro C Izidoro +2
This work proposes the use of Genetic Algorithms (GA) to identify the area of the breast from the background in thermographic breast images. The proposed method uses color informat…
Fractal triangular search: a metaheuristic for image content search
Erick O. Rodrigues, Panos Liatsis, Luiz Satoru +1
This work proposes a variable neighbourhood search (FTS) that uses a fractal-based local search primarily designed for images. Searching for specific content in images is posed as…
Local-sensitive connectivity filter (ls-cf): A post-processing unsupervised improvement of the frangi, hessian and vesselness filters for multimodal vessel segmentation
Erick O Rodrigues, Lucas O Rodrigues, João HP Machado +5
A retinal vessel analysis is a procedure that can be used as an assessment of risks to the eye. This work proposes an unsupervised multimodal approach that improves the response of…
ELEMENT: Multi-Modal Retinal Vessel Segmentation Based on a Coupled Region Growing and Machine Learning Approach
Erick O. Rodrigues, Aura Conci, Panos Liatsis
Vascular structures in the retina contain important information for the detection and analysis of ocular diseases, including age-related macular degeneration, diabetic retinopathy…
Proposal and study of statistical features for string similarity computation and classification
E. O. Rodrigues, D. Casanova, M. Teixeira +5
Adaptations of features commonly applied in the field of visual computing, co-occurrence matrix (COM) and run-length matrix (RLM), are proposed for the similarity computation of st…
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…
Spatially-resolved Thermometry from Line-of-Sight Emission Spectroscopy via Machine Learning
Ruiyuan Kang, Dimitrios C. Kyritsis, Panos Liatsis
A methodology is proposed, which addresses the caveat that line-of-sight emission spectroscopy presents in that it cannot provide spatially resolved temperature measurements in non…
Flame-state monitoring based on very low number of visible or infrared images via few-shot learning
Ruiyuan Kang, Panos Liatsis, Dimitrios C. Kyritsis
The current success of machine learning on image-based combustion monitoring is based on massive data, which is costly even impossible for industrial applications. To address this…
Self-Validated Physics-Embedding Network: A General Framework for Inverse Modelling
Ruiyuan Kang, Dimitrios C. Kyritsis, Panos Liatsis
Physics-based inverse modeling techniques are typically restricted to particular research fields, whereas popular machine-learning-based ones are too data-dependent to guarantee th…
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…
Machine learning in the prediction of cardiac epicardial and mediastinal fat volumes
É. O. Rodrigues, V. H. A. Pinheiro, P. Liatsis +1
We propose a methodology to predict the cardiac epicardial and mediastinal fat volumes in computed tomography images using regression algorithms. The obtained results indicate that…
A Novel Transformer Network with Shifted Window Cross-Attention for Spatiotemporal Weather Forecasting
Alabi Bojesomo, Hasan Al Marzouqi, Panos Liatsis
Earth Observatory is a growing research area that can capitalize on the powers of AI for short time forecasting, a Now-casting scenario. In this work, we tackle the challenge of we…
Multi-Label Retinal Disease Classification using Transformers
M. A. Rodriguez, H. AlMarzouqi, P. Liatsis
Early detection of retinal diseases is one of the most important means of preventing partial or permanent blindness in patients. In this research, a novel multi-label classificatio…
Traffic4cast at NeurIPS 2021 -- Temporal and Spatial Few-Shot Transfer Learning in Gridded Geo-Spatial Processes
Christian Eichenberger, Moritz Neun, Henry Martin +34
The IARAI Traffic4cast competitions at NeurIPS 2019 and 2020 showed that neural networks can successfully predict future traffic conditions 1 hour into the future on simply aggrega…
SwinUNet3D -- A Hierarchical Architecture for Deep Traffic Prediction using Shifted Window Transformers
Alabi Bojesomo, Hasan Al Marzouqi, Panos Liatsis
Traffic forecasting is an important element of mobility management, an important key that drives the logistics industry. Over the years, lots of work have been done in Traffic fore…
Morphological classifiers
É. O. Rodrigues, A. Conci, P. Liatsis
This work proposes a new type of classifier called Morphological Classifier (MC). MCs aggregate concepts from mathematical morphology and supervised learning. The outcomes of this…
Traffic flow prediction using Deep Sedenion Networks
Alabi Bojesomo, Panos Liatsis, Hasan Al Marzouqi
In this paper, we present our solution to the Traffic4cast2020 traffic prediction challenge. In this competition, participants are to predict future traffic parameters (speed and v…