| | --- |
| | language: |
| | - en |
| | tags: |
| | - image-classification |
| | license: mit |
| | datasets: |
| | - imagenet |
| | --- |
| | |
| |
|
| | # Change Detection Models for National Infrastructure Monitoring |
| |
|
| | This repository contains a collection of Fine-tuned change detection models developed by Team-1 from San Jose State University as part of the National Infrastructure Monitoring project. |
| |
|
| | ## Models and Contributors |
| |
|
| | Our team has implemented several state-of-the-art change detection models: |
| |
|
| | 1. **ChangeViT**: Built by Nihar |
| | - Combines Vision Transformer (ViT) and CNN architectures |
| | - Excels at detecting both large-scale and fine-grained changes |
| | - [Nihar's LinkedIn](https://www.linkedin.com/in/nihar-palem-1b955a183/) |
| |
|
| | 2. **BITCD**: Developed by Charishma |
| | - Uses a transformer-based approach for advanced change detection |
| | - Processes images as compact token sets for improved efficiency |
| | - [Charishma's LinkedIn](https://www.linkedin.com/in/sai-charishma-kurmala-080983128/) |
| |
|
| | 3. **ChangeFormer**: Implemented by Keerthana |
| | - Transformer-based architecture for satellite imagery change detection |
| | - Captures long-range spatial and temporal dependencies |
| | - [Keerthana's LinkedIn](https://www.linkedin.com/in/keerthana-raskatla-1573781a4/) |
| |
|
| | 4. **Multi-Modal Adaptation Network**: Content generation by Anbu |
| | - Combines optical and SAR imagery for robust change detection |
| | - Utilizes domain adaptation to align features from different image types |
| | - [Anbu's LinkedIn](https://www.linkedin.com/in/anbuvalluvan/) |
| |
|
| | 5. **Siamese Nested UNet**: Developed by Harika |
| | - Combines Siamese network and U-Net architectures |
| | - Excels at image comparison tasks for change detection |
| | - [Harika's LinkedIn](https://www.linkedin.com/in/harika-boyina/) |
| |
|
| | ## Key Features |
| |
|
| | - Advanced change detection capabilities for high-resolution satellite imagery |
| | - Utilization of transformer-based approaches for capturing long-range relationships |
| | - Efficient processing of large-scale datasets |
| | - Combination of multiple imaging modalities for improved accuracy |
| | - Scalability to handle various image sizes and resolutions |
| |
|
| | These models represent cutting-edge approaches in remote sensing and change detection, specifically tailored for national infrastructure monitoring applications. |
