Ioannis D. Apostolopoulos
Orcid: 0000-0001-6439-9282
According to our database1,
Ioannis D. Apostolopoulos
authored at least 22 papers
between 2020 and 2024.
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Bibliography
2024
A Multi-Modal Machine Learning Methodology for Predicting Solitary Pulmonary Nodule Malignancy in Patients Undergoing PET/CT Examination.
Big Data Cogn. Comput., August, 2024
Calibration and Inter-Unit Consistency Assessment of an Electrochemical Sensor System Using Machine Learning.
Sensors, July, 2024
2023
Industrial object and defect recognition utilizing multilevel feature extraction from industrial scenes with Deep Learning approach.
J. Ambient Intell. Humaniz. Comput., 2023
An Attention-Based Deep Convolutional Neural Network for Brain Tumor and Disorder Classification and Grading in Magnetic Resonance Imaging.
Inf., 2023
CoRR, 2023
Explainable Artificial Intelligence Method (ParaNet+) Localises Abnormal Parathyroid Glands in Scintigraphic Scans of Patients with Primary Hyperparathyroidism.
Algorithms, 2023
Explainable Classification for Non-Small Cell Lung Cancer Based on Positron Emission Tomography Features and Clinical Data.
Proceedings of the 14th International Conference on Information, 2023
Deep Fuzzy Cognitive Map methodology for Non-Small Cell Lung Cancer diagnosis based on Positron Emission Tomography imaging.
Proceedings of the 14th International Conference on Information, 2023
Abnormal Parathyroid Gland Localization in Scintigraphic Images Using a Vision Transformer Network.
Proceedings of the 14th International Conference on Information, 2023
A Fuzzy Cognitive Map Learning Approach for Coronary Artery Disease Diagnosis in Nuclear Medicine.
Proceedings of the Fuzzy Logic and Technology, and Aggregation Operators, 2023
2022
Artificial Intelligence Methods for Identifying and Localizing Abnormal Parathyroid Glands: A Review Study.
Mach. Learn. Knowl. Extr., December, 2022
An Explainable Deep Learning Framework for Detecting and Localising Smoke and Fire Incidents: Evaluation of Grad-CAM++ and LIME.
Mach. Learn. Knowl. Extr., December, 2022
Detection and Localisation of Abnormal Parathyroid Glands: An Explainable Deep Learning Approach.
Algorithms, 2022
Towards an Internet of Things application for the prognosis of Coronary Artery Disease using Machine Learning and Fuzzy Logic.
Proceedings of the 13th International Conference on Information, 2022
Solitary Pulmonary Nodule malignancy classification utilising 3D features and semi-supervised Deep Learning.
Proceedings of the 13th International Conference on Information, 2022
An IoT Integrated Air Quality Monitoring Device Based on Microcomputer Technology and Leading Industry Low-Cost Sensor Solutions.
Proceedings of the Future Access Enablers for Ubiquitous and Intelligent Infrastructures, 2022
2021
Automatic classification of solitary pulmonary nodules in PET/CT imaging employing transfer learning techniques.
Medical Biol. Eng. Comput., 2021
2020
Industrial object, machine part and defect recognition towards fully automated industrial monitoring employing deep learning. The case of multilevel VGG19.
CoRR, 2020
State Space Advanced Fuzzy Cognitive Map approach for automatic and non Invasive diagnosis of Coronary Artery Disease.
CoRR, 2020
Non-invasive modelling methodology for the diagnosis of Coronary Artery Disease using Fuzzy Cognitive Maps.
CoRR, 2020
Covid-19: Automatic detection from X-Ray images utilizing Transfer Learning with Convolutional Neural Networks.
CoRR, 2020
Experimenting with Convolutional Neural Network Architectures for the automatic characterization of Solitary Pulmonary Nodules' malignancy rating.
CoRR, 2020