Effective image synthesis for effective deep neural network training
State-of-the-art deep neural networks (DNNs) necessitate a significant number of images to achieve accurate and robust models. However, gathering a large amount of images remains the prevailing approach, which proves expensive, time-consuming, and challenging to scale across different tasks and d...
Saved in:
主要作者: | Cui, Kaiwen |
---|---|
其他作者: | Lu Shijian |
格式: | Thesis-Doctor of Philosophy |
語言: | English |
出版: |
Nanyang Technological University
2024
|
主題: | |
在線閱讀: | https://hdl.handle.net/10356/174934 |
標簽: |
添加標簽
沒有標簽, 成為第一個標記此記錄!
|
相似書籍
-
Deep graph neural networks for link prediction
由: Zheng, MingXi
出版: (2024) -
Study of fine-tuning the pre-trained deep convolutional neural networks for image recognition
由: Nur Azila Azman
出版: (2020) -
Learning deep networks for image classification
由: Zhou, Yixuan
出版: (2024) -
Learning deep networks for image segmentation
由: Akash, T
出版: (2024) -
Effects of incremental training on watermarked neural networks
由: Heng, Chuan Song
出版: (2023)