A5059739238- Radiomics and Machine Learning in Medical Imaging
- AI in cancer detection
- Artificial Intelligence in Healthcare and Education
- Advanced Image and Video Retrieval Techniques
- Generative Adversarial Networks and Image Synthesis
- Face and Expression Recognition
- Advanced Neural Network Applications
- Emotion and Mood Recognition
- Digital Radiography and Breast Imaging
- Computer Graphics and Visualization Techniques
- Face recognition and analysis
- 3D Shape Modeling and Analysis
- Vehicle License Plate Recognition
Universitat de Girona
2024
Eskisehir Technical University
2021-2022
Deep learning has achieved impressive performance across various medical imaging tasks. However, its inherent bias against specific groups hinders clinical applicability in equitable healthcare systems. A recently discovered phenomenon, Neural Collapse (NC), shown potential improving the generalization of state-of-the-art deep models. Nonetheless, implications on remain unexplored. Our study investigates fairness through lens NC. We analyze training dynamics models as they approach NC when...
In the field of transportation and logistics, smart vision systems have been employed successfully to automate various tasks such as number-plate recognition vehicle identity recognition. The development automated is possible with availability large image datasets having proper annotations. TRODO dataset a rich-annotated collection odometer displays that can enable automatic mileage reading from raw images. Initially, consisted 2613 frames captured in different conditions terms resolution,...
The use of video conferencing tools in education has increased dramatically recent years. Especially after the COVID-19 outbreak, many classes have been moved to online platforms due social distancing precautions. While this trend eliminates physical dependencies and provides a continuous educational environment, it also creates some problems long term. Primarily, instructors students reported issues concerning lack emotional interaction between participants. During in-place education,...
Accurate 3D modeling of human organs plays a crucial role in building computational phantoms for virtual imaging trials. However, generating anatomically plausible reconstructions organ surfaces from computed tomography scans remains challenging many structures the body. This challenge is particularly evident when dealing with large intestine. In this study, we leverage recent advancements geometric deep learning and denoising diffusion probabilistic models to refine segmentation results We...