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Upernet Tu Resnet18
UPerNet is an image segmentation model implemented in PyTorch, supporting semantic segmentation tasks.
Downloads 267
Release Time : 12/23/2024
Model Overview
UPerNet is an efficient semantic segmentation model suitable for various image segmentation tasks, such as scene understanding and medical image analysis.
Model Features
Flexible Encoder Selection
Supports multiple pre-trained encoders (e.g., ResNet) and can be flexibly chosen based on task requirements.
Efficient Decoder Design
Utilizes an optimized decoder structure to improve segmentation accuracy and inference speed.
Easy Integration
Provides a simple API for easy integration with other PyTorch projects.
Model Capabilities
Image Segmentation
Semantic Segmentation
Scene Understanding
Use Cases
Computer Vision
Scene Segmentation
Used for road and obstacle segmentation in autonomous driving.
Medical Image Analysis
Used for organ or lesion segmentation in medical images.
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