MUnet-LUC

Land Use Classification with mUnet by Abhishek and Sayon

Description

We aimed at developing a deep learning Pipeline to classify land use types from satellite images.
Land Use can be classified into following classes-

1. Buildings
2. Trees
3. Crops
4. Roads & Tracks
5. Water
6. Empty Fields

Model Overview

We used the paper by Lakshya Garg et al to implement their proposed Modified UNet Architecture for Land Use Classification of Satellite Imagery

Modified UNet Architecture

Results and Inference

Model was trained on Colab's 12GB NVIDIA Tesla K80 GPU for 150 epochs
with training accuracy of 80.037%

Model	$Parameters	Accuracy
AlexNet	61,000,000	78.234%
UNet	31,379,205	62.1077%
mUnet	31,105,669	80.897%

Applications

Smart City Planning (Searching Construction Space, Monitoring Vegetation etc.)

Defence Applications

Natural Resource Monitoring and Management ✓Disaster Management