Pan Tu Resnet18
PAN is an image segmentation model implemented in PyTorch, utilizing pyramid attention mechanisms to enhance feature extraction capabilities
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Release Time : 12/23/2024
Model Overview
A deep learning model for semantic segmentation tasks, supporting various encoder architectures, suitable for segmentation scenarios such as medical imaging and satellite imagery
Model Features
Pyramid Attention Mechanism
Enhances the representation capability of feature pyramids through multi-scale attention modules
Flexible Encoder Selection
Supports mainstream encoder architectures like ResNet, with the ability to load ImageNet pre-trained weights
Lightweight Design
Default configuration requires only 32 decoder channels, making it suitable for resource-constrained scenarios
Model Capabilities
Image Semantic Segmentation
Multi-class Pixel-level Classification
Medical Image Analysis
Satellite Image Parsing
Use Cases
Medical Imaging
Organ Segmentation
Segmentation of organ tissues in CT/MRI images
Remote Sensing
Land Cover Classification
Segmentation of vegetation/buildings/water bodies in satellite images
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