AIbase
EN
Home
Aggregate Segmentation
A

Aggregate Segmentation

Developed by Matiullah2401592
PyTorch-based DeepLabV3Plus image segmentation model supporting efficient semantic segmentation tasks
Image Segmentation
Safetensors
Open Source License:MIT#Efficient Semantic Segmentation#Multi-scale Dilated Convolution#Medical Image Analysis
Downloads 78
Release Time : 4/9/2025

Model Overview

DeepLabV3Plus is an advanced semantic segmentation model that combines deep convolutional neural networks with Atrous Spatial Pyramid Pooling (ASPP) modules, enabling efficient pixel-level image segmentation.

Model Features

Efficient Encoder
Uses EfficientNet-b5 as the encoder to reduce computational resource requirements while maintaining high performance
Atrous Spatial Pyramid Pooling
Employs ASPP modules to capture multi-scale contextual information and improve segmentation accuracy
Separable Convolution
Uses separable convolution in the decoder to reduce model complexity
Pre-trained Support
Supports initialization with ImageNet pre-trained weights

Model Capabilities

Image Semantic Segmentation
Pixel-level Classification
Multi-scale Feature Extraction

Use Cases

Medical Imaging
Organ Segmentation
Segment specific organs or tissues in CT or MRI scans
Autonomous Driving
Road Scene Understanding
Segment key elements such as roads, pedestrians, and vehicles
Remote Sensing
Land Use Classification
Perform land cover type segmentation on satellite images
Featured Recommended AI Models
AIbase
Empowering the Future, Your AI Solution Knowledge Base
EnglishįŽ€äŊ“中文įšéĢ”中文ãĢãģんご
Š 2025AIbase