Browsing by Titles

Showing results 1 to 10 of 10

  • Seungjun Lee
  • 2024
  • Seungjun Lee. (2024). A study of quadratic discriminant analysis-based motor imagery classification using functional near- infrared spectroscopy. doi: 10.22677/THESIS.200000731466
  • DGIST
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  • Sungwoo Son
  • 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 : 293
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  • Eunji Kim
  • 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
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  • Joonbeom Kim
  • 2023
  • Joonbeom Kim. (2023). Development of bench-top photon-counting CT system and its application to calibration-based material decomposition. doi: 10.22677/THESIS.200000657362
  • DGIST
  • View : 139
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  • Taiin Eom
  • 2023
  • Taiin Eom. (2023). Development of DOT-based fNIRS-BCI technology with high recognition rate. doi: 10.22677/THESIS.200000657930
  • DGIST
  • View : 249
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  • Jeonghyeon Nam
  • 2021
  • Jeonghyeon Nam. (2021). Fast and accurate photon-counting detector-based material decomposition via nearest neighborhood method. doi: 10.22677/thesis.200000363790
  • DGIST
  • View : 220
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  • Jihyeon Kim
  • 2024
  • Jihyeon Kim. (2024). Incremental Learning to Segment Multiple Organs Using DeepInversion. doi: 10.22677/THESIS.200000802008
  • DGIST
  • View : 124
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  • Kihwan Kim
  • 2021
  • Kihwan Kim. (2021). Log-ratio measurements-based accurate non-iterative algorithm in diffuse optical tomography for sparsely localized optical parameter variations. doi: 10.22677/thesis.200000362068
  • DGIST
  • View : 156
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  • Tashfeen Abdul Muqeet Bin
  • 2023
  • Tashfeen Abdul Muqeet Bin. (2023). Unsupervised Anomaly Detection Using Self-Supervised Learning with Knowledge Distillation. doi: 10.22677/THESIS.200000653398
  • DGIST
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  • Jinmin Kim
  • 2023
  • Jinmin Kim. (2023). Virtual Jawbone Reduction Planning based on Dental Occlusion for Mandibular Fracture Surgery. doi: 10.22677/THESIS.200000653799
  • DGIST
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