Showing results 1 to 11 of 11
- 2024
- Beaungwoon Moon. (2024). Anonymous authentication system based on complex sinusoidal waveform. doi: 10.22677/THESIS.200000799391
- DGIST
- View : 133
- Download : 0
- 2025
- Ongee Jeong. (2025). Automated Analysis of Encrypted and Obfuscated Data based on Deep Neural Networks. doi: 10.22677/THESIS.200000841197
- DGIST
- View : 87
- Download : 0
- 2022
- Sungwoo Son. (2022). Automated image-based classification of cancer cell by using digital holography and deep learning. doi: 10.22677/thesis.200000595277
- DGIST
- View : 296
- Download : 0
- 2024
- Jaewon Jeong. (2024). Automated Multi-Class Segmentation for Myotube Morphology in Fluorescent Images Using Deep Learning. doi: 10.22677/THESIS.200000730427
- DGIST
- View : 129
- Download : 0
- 2021
- Eunji Kim. (2021). Deep learning-based automated analysis of red blood cells three-dimensional morphological changes in the storage lesion. doi: 10.22677/thesis.200000364438
- DGIST
- View : 231
- Download : 0
- 2025
- Sangheon Jeong. (2025). Knowledge Transfer Methods for Photon Counting Double Random Phase Encoded Image Classification. doi: 10.22677/THESIS.200000828394
- DGIST
- View : 254
- Download : 0
- 2023
- Namki Kim. (2023). Missing Ciphertext Recovery and Classification via Deep Learning. doi: 10.22677/THESIS.200000656454
- DGIST
- View : 265
- Download : 0
- 2020
- Seunghyeon Hwang. (2020). New phase unwrapping approach in digital holographic microscopy with deep learning. doi: 10.22677/Theses.200000285033
- DGIST
- View : 665
- Download : 0
- 2025
- Hyunbin An. (2025). Optimized Red Blood Cell Segmentation in Holographic Imaging through Integration of Self-Supervised Learning and Diffusion Models. doi: 10.22677/THESIS.200000828659
- DGIST
- View : 132
- Download : 0
- 2020
- Minwoo Sim. (2020). Red blood cell study at different temperatures with holographic imaging informatics. doi: 10.22677/Theses.200000285143
- DGIST
- View : 562
- Download : 184
- 2023
- Rehman Abdur. (2023). Self-Supervised Learning in Holographic Image Analysis for Biomedical Applications. doi: 10.22677/THESIS.200000656707
- DGIST
- View : 235
- Download : 0
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