摘要
To apply convolutional neural networks (CNNs) on high-resolution images, a common approach is to split the input image into smaller patches. However, the field-of-view is restricted by the input size. To overcome the problem, a multi-magnification attention convolutional neural network (MMA-CNN) is proposed to analyze images based on both local and global features. Our approach focuses on identifying the importance of individual features at each magnification level and is applied to pathology whole slide images (WSIs) segmentation to show its effectiveness. Several interactive figures are also developed to enhance the reader's understanding of our research.
原文 | English |
---|---|
頁(從 - 到) | 54-55 |
頁數 | 2 |
期刊 | IEEE Computational Intelligence Magazine |
卷 | 18 |
發行號 | 3 |
DOIs | |
出版狀態 | Published - 2023 8月 1 |
All Science Journal Classification (ASJC) codes
- 理論電腦科學
- 人工智慧