For state-of-the-art image segmentation, consider these top algorithms:
- U-Net: Widely used for medical imaging with an encoder-decoder structure.
- Mask R-CNN: Combines object detection and instance segmentation.
- DeepLabv3+: Uses atrous convolution for capturing fine details in semantic segmentation.
- HRNet: Maintains high-resolution representations, great for spatial detail.
- Swin Transformer: A vision transformer offering a balance between accuracy and efficiency.
Choose based on task requirements, data characteristics, and available computational resources.
