SegFormer-b5-Andhra-Landuse
SegFormer-B5 fine-tuned on 20,000+ Sentinel-2 satellite image chips from 5 districts of Andhra Pradesh, India. Supports land use semantic segmentation (Buildings, Roads, Water Bodies, Open Plots) and bi-temporal change detection. Best mIoU: 0.5474.
.png){kind=small}
About Model
This model is a SegFormer-B5 architecture fine-tuned for semantic land use segmentation and bi-temporal change detection on Sentinel-2 satellite imagery covering 5 districts of Andhra Pradesh, India. Developed by Yantrikaran Innovations Pvt. Ltd. for smart property identification and land analytics for the Andhra Pradesh government. CAPABILITIES: 1. Land Use Segmentation — classifies each pixel into 5 classes from a single satellite tile. 2. Change Detection — detects land use changes between two temporal satellite images (new construction, encroachment, deforestation). CLASSES: - Background (IoU: 0.880) - Buildings (IoU: 0.430) - Road (IoU: 0.431) - Water Body (IoU: 0.635) - Open Plot (IoU: 0.281) TRAINING DETAILS: - Architecture: SegFormer-B5 - Dataset: 20,000+ chips, 5 districts of Andhra Pradesh - Image Source: Sentinel-2 MSI (Multispectral Instrument) - Chip Size: 512x512 px - Total Epochs: 60 | Best Epoch: 56 - Best mIoU: 0.5474 - Training Loss: 0.8196 | Validation Loss: 0.8482 - Early Stopping Patience: 10 epochs - Also hosted at: https://huggingface.co/yantrikaran-innovations/segformer-b5-andhra-landuse
SegFormer-b5-Andhra-Landuse
Metadata
Apache 2.0
yantrikaran-innovations
Semantic Segmentation Model
PyTorch
Open
Housing, Urban Planning and Infrastructure
30/04/26 10:14:41
0
Activity Overview
0
0 
0 
8
Tags
- Remote Sensing
- Satellite Imagery
- Urban Planning
- Andhra Pradesh
- geospatial
- semantic-segmentation
- land-use-classification
- segformer
- change-detection
- property-identification
License Control
Apache 2.0
More Models from Yantrikaran Innovations Private Limited
- 0
- 0
- 0
9
© 2026 - Copyright AIKosh. All rights reserved.