About this document
Hybrid U-Net ResNet for Wound Segmentation by Tarik Rahman is a document available to read on EtoBox.
The document presents research on an automated wound care system utilizing a hybrid deep learning framework that combines U-Net and ResNet34 for improved wound segmentation. The study demonstrates high performance metrics, achieving an Intersection over Union (IoU) of 0.973 and a Dice coefficient of 0.986, indicating precise segmentation. The methodology and dataset used are publicly available, highlighting the potential applicability of this approach in various medical imaging tasks.
- Author
- Tarik Rahman
- Language
- EN