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Journal Articles
- 2023
[j1]Theodora Sanida
, Irene-Maria Tabakis, Maria Vasiliki Sanida, Argyrios Sideris, Minas Dasygenis:
A Robust Hybrid Deep Convolutional Neural Network for COVID-19 Disease Identification from Chest X-ray Images. Inf. 14(6): 310 (2023)
Conference and Workshop Papers
- 2024
- [c7]Maria Vasiliki Sanida, Theodora Sanida, Argyrios Sideris, Michael F. Dossis, Minas Dasygenis:
Fake News Detection Approach Using Hybrid Deep Learning Framework. SEEDA-CECNSM 2024: 81-84 - [c6]Theodora Sanida, Argyrios Sideris, Maria Vasiliki Sanida, Michael F. Dossis, Minas Dasygenis:
Accelerating CNNs for Pneumonia Disease Diagnosis via Heterogeneous FPGA Systems. SEEDA-CECNSM 2024: 159-162 - 2023
- [c5]Theodora Sanida, Maria Vasiliki Sanida, Argyrios Sideris, Minas Dasygenis:
A Lightweight CNN Model for Tomato Crop Diseases on Heterogeneous Embedded System. MOCAST 2023: 1-4 - [c4]Theodora Sanida, Maria Vasiliki Sanida, Argyrios Sideris, Michael Dossis, Minas Dasygenis:
Efficient Categorization of Pneumonia Diagnosis Using Low-Power Embedded Devices. SEEDA-CECNSM 2023: 1-4 - [c3]Theodora Sanida, Argyrios Sideris, Maria Vasiliki Sanida, Michael Dossis, Minas Dasygenis:
An Efficiency CNN Solution for Olive Disease Management Through FPGA. SEEDA-CECNSM 2023: 1-4 - [c2]Theodora Sanida, Argyrios Sideris, Maria Vasiliki Sanida, Michael Dossis, Minas Dasygenis:
Acceleration of GANs for Potato Crop Disease Identification via FPGA. SEEDA-CECNSM 2023: 1-4 - [c1]Argyrios Sideris, Theodora Sanida, Maria Vasiliki Sanida, Michael Dossis, Minas Dasygenis:
Accelerate Processing of Image with the Keccak-512 Algorithm on Cryptoprocessor. SEEDA-CECNSM 2023: 1-4
Coauthor Index
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