Panagiotis Gonidakis

According to our database, Panagiotis Gonidakis authored at least 7 papers between 2020 and 2025.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2025

Evaluating Four FPGA-Accelerated Space Use Cases Based on Neural Network Algorithms for On-Board Inference.

Pedro Antunes, Muhammad Ihsan Al Hafiz, Jonah Ekelund, Ekaterina Dineva, George Miloshevich, Panagiotis Gonidakis, Artur Podobas

Proceedings of the 18th IEEE International Symposium on Embedded Multicore/Many-core Systems-on-Chip, 2025

2024

The STOIC2021 COVID-19 AI challenge: Applying reusable training methodologies to private data.

Luuk H. Boulogne, Julian Lorenz, Daniel Kienzle, Robin Schön, Katja Ludwig, Rainer Lienhart, Simon Jégou, Guang Li, Cong Chen, Qi Wang, Derik Shi, Mayug Maniparambil, Dominik Müller, Silvan Mertes, Niklas Schröter, Fabio Hellmann, Miriam Elia, Ine Dirks, Matías Nicolás Bossa, Abel Díaz Berenguer, Tanmoy Mukherjee, Jef Vandemeulebroucke, Hichem Sahli, Nikos Deligiannis, Panagiotis Gonidakis, Ngoc Dung Huynh, Imran Razzak, Mohamed Reda Bouadjenek, Mario Verdicchio, Pasquale Borrelli, Marco Aiello, James A. Meakin, Alexander Lemm, Christoph Russ, Razvan Ionasec, Nikos Paragios, Bram van Ginneken, Marie-Pierre Revel

Medical Image Anal., 2024

2023

Handcrafted Features Can Boost Performance and Data-Efficiency for Deep Detection of Lung Nodules From CT Imaging.

Panagiotis Gonidakis, Alexander Sóñora-Mengana, Bart Jansen, Jef Vandemeulebroucke

IEEE Access, 2023

2020

Explainable-by-design Semi-Supervised Representation Learning for COVID-19 Diagnosis from CT Imaging.

Abel Díaz Berenguer, Hichem Sahli, Boris Joukovsky, Maryna Kvasnytsia, Ine Dirks, Mitchel Alioscha-Pérez, Nikos Deligiannis, Panagiotis Gonidakis, Sebastián Amador Sánchez, Redona Brahimetaj, Evgenia Papavasileiou, Jonathan Cheung-Wai Chan, Fei Li, Shangzhen Song, Yixin Yang, Sofie Tilborghs, Siri Willems, Tom Eelbode, Jeroen Bertels, Dirk Vandermeulen, Frederik Maes, Paul Suetens, Lucas Fidon, Tom Vercauteren, David Robben, Arne Brys, Dirk Smeets, Bart Ilsen, Nico Buls, Nina Watté, Johan de Mey, Annemiek Snoeckx, Paul M. Parizel, Julien Guiot, Louis Deprez, Paul Meunier, Stefaan Gryspeerdt, Kristof De Smet, Bart Jansen, Jef Vandemeulebroucke

CoRR, 2020

Comparative study of deep learning methods for the automatic segmentation of lung, lesion and lesion type in CT scans of COVID-19 patients.

Sofie Tilborghs, Ine Dirks, Lucas Fidon, Siri Willems, Tom Eelbode, Jeroen Bertels, Bart Ilsen, Arne Brys, Adriana Dubbeldam, Nico Buls, Panagiotis Gonidakis, Sebastián Amador Sánchez, Annemiek Snoeckx, Paul M. Parizel, Johan de Mey, Dirk Vandermeulen, Tom Vercauteren, David Robben, Dirk Smeets, Frederik Maes, Jef Vandemeulebroucke, Paul Suetens

CoRR, 2020

Evaluating several ways to combine handcrafted features-based system with a deep learning system using the LUNA16 Challenge framework.

Alexander Sóñora-Mengana, Panagiotis Gonidakis, Bart Jansen, Juan Carlos García-Naranjo, Jef Vandemeulebroucke

Proceedings of the Medical Imaging 2020: Computer-Aided Diagnosis, 2020

Artificially augmenting data or adding more samples? A study on a 3D CNN for lung nodule classification.

Panagiotis Gonidakis, Bart Jansen, Jef Vandemeulebroucke

Proceedings of the Medical Imaging 2020: Computer-Aided Diagnosis, 2020