Showing results 1 to 13 of 13
- 2021
- Keonwoo Noh. (2021). A deep learning method for chamber enlargement diagnosis. doi: 10.22677/thesis.200000366283
- DGIST
- View : 272
- Download : 0
- 2021
- Ilseop Lee. (2021). A Delete-Aware Compaction Trigger Method for LSM-Tree Based Key-Value Stores. doi: 10.22677/thesis.200000364341
- DGIST
- View : 329
- Download : 335
- 2022
- Juyeong Jeong. (2022). A Fast Distributed HyperLedger Fabric using Adaptive State Synchronization. doi: 10.22677/thesis.200000592087
- DGIST
- View : 303
- Download : 0
- 2025
- Jihye Lee. (2025). A Memory-Efficient and Scalable GPU-Based Tucker Decomposition Method for Large-Scale Tensors. doi: 10.22677/THESIS.200000841755
- DGIST
- View : 166
- Download : 0
- 2023
- Hajin Jeon. (2023). A Method for Rapid Design of High-quality Primers for PCR Experiments. doi: 10.22677/THESIS.200000653897
- DGIST
- View : 381
- Download : 0
- 2021
- Jinwook Kim. (2021). An Effective and Efficient Method for Tweaking Deep Neural Networks. doi: 10.22677/thesis.200000497154
- DGIST
- View : 253
- Download : 105
- 2019
- Himchan Park. (2019). An efficient and effective method for generating trillion-scale synthetic graphs. doi: 10.22677/thesis.200000217215
- DGIST
- View : 604
- Download : 0
- 2023
- Heechul Lim. (2023). Community-based methods for neural architecture search and knowledge base population. doi: 10.22677/THESIS.200000684740
- DGIST
- View : 234
- Download : 0
- 2021
- Hyun-Lim Yang. (2021). Exploiting the Intermediate Layers of Convolutional Neural Networks for Medical Deep Learning. doi: 10.22677/thesis.200000362649
- DGIST
- View : 268
- Download : 0
- 2021
- Eunjeong Yi. (2021). Exploiting various patterns for heterogeneous graph attention network. doi: 10.22677/thesis.200000497156
- DGIST
- View : 199
- Download : 121
- 2019
- Yoon-Min Nam. (2019). Fast and Memory-Efficient Query Processing SysteMaster for Complex OLAP Databases and Queries. doi: 10.22677/thesis.200000220645
- DGIST
- View : 643
- Download : 0
- 2021
- Myeonghwa Lee. (2021). Improving the Performance of Natural Language Deep Learning Models by Using Dimension Attribute Values. doi: 10.22677/thesis.200000363154
- DGIST
- View : 195
- Download : 0
- 2019
- Sanghyeon Lee. (2019). Multimodal Data Management in Disks and Main Memory for Deep Learning. doi: 10.22699/thesis.200000171479
- DGIST
- View : 457
- Download : 0
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