{"id":24811774,"url":"https://github.com/al-chris/satelliteimageclassification","last_synced_at":"2026-04-18T01:31:41.552Z","repository":{"id":197453554,"uuid":"698683793","full_name":"al-chris/satelliteImageClassification","owner":"al-chris","description":"Python and MATLAB codes for satellite image classification using a convolutional neural network.","archived":false,"fork":false,"pushed_at":"2024-12-31T18:03:01.000Z","size":158,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-10-08T12:42:33.844Z","etag":null,"topics":["cnn","deep-learning","deep-neural-networks","image-classification","matlab","tensorflow"],"latest_commit_sha":null,"homepage":"","language":"Jupyter Notebook","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"mit","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/al-chris.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null,"zenodo":null,"notice":null,"maintainers":null,"copyright":null,"agents":null,"dco":null,"cla":null}},"created_at":"2023-09-30T16:39:28.000Z","updated_at":"2025-01-12T18:39:59.000Z","dependencies_parsed_at":null,"dependency_job_id":"e82f82eb-d17b-4b11-8717-84d8105f5195","html_url":"https://github.com/al-chris/satelliteImageClassification","commit_stats":null,"previous_names":["al-chris/satelliteimageclassification"],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/al-chris/satelliteImageClassification","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/al-chris%2FsatelliteImageClassification","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/al-chris%2FsatelliteImageClassification/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/al-chris%2FsatelliteImageClassification/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/al-chris%2FsatelliteImageClassification/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/al-chris","download_url":"https://codeload.github.com/al-chris/satelliteImageClassification/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/al-chris%2FsatelliteImageClassification/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":31953509,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-04-18T00:39:45.007Z","status":"ssl_error","status_checked_at":"2026-04-18T00:39:20.671Z","response_time":62,"last_error":"SSL_read: unexpected eof while reading","robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":false,"can_crawl_api":true,"host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["cnn","deep-learning","deep-neural-networks","image-classification","matlab","tensorflow"],"created_at":"2025-01-30T13:16:19.228Z","updated_at":"2026-04-18T01:31:41.525Z","avatar_url":"https://github.com/al-chris.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"# satelliteImageClassification\nPython and MATLAB codes for satellite image classification using a convolutional neural network.\n\nThe dataset used was gotten from\n\nhttps://www.kaggle.com/datasets/mahmoudreda55/satellite-image-classification\n\n\n# Image Classification Repository\n\nThis repository contains Python and MATLAB code for classifying satellite images using a convolutional neural network (CNN). The dataset used is available at [Kaggle: Satellite Image Classification](https://www.kaggle.com/datasets/mahmoudreda55/satellite-image-classification).\n\n## Project Overview\n\nThe project demonstrates how to build and train a CNN to classify satellite images. It includes:\n\n- **Data Preprocessing**: Loading and preparing the dataset for training.\n- **Model Architecture**: Defining the CNN structure.\n- **Training**: Training the model on the dataset.\n- **Evaluation**: Assessing the model's performance on test data.\n\n## Repository Structure\n\n- `LICENSE`: License information.\n- `README.md`: Project overview and instructions.\n- `satellite.ipynb`: Jupyter Notebook with Python code for training and evaluating the CNN.\n- `satellite_images.mlx`: MATLAB Live Script for training and evaluating the CNN.\n\n## Getting Started\n\nTo run the code:\n\n1. **Clone the repository**:\n\n   ```bash\n   git clone https://github.com/al-chris/satelliteImageClassification.git\n   ```\n\n2. **Navigate to the project directory**:\n\n   ```bash\n   cd satelliteImageClassification\n   ```\n\n3. **Install the required Python packages**:\n\n   Ensure you have Python installed, then install the necessary packages:\n\n   ```bash\n   pip install -r requirements.txt\n   ```\n\n   *Note: The `requirements.txt` file should list all required packages. If it's missing, refer to the imports in `satellite.ipynb` and install the packages manually.*\n\n4. **Download the dataset**:\n\n   Download the dataset from [Kaggle](https://www.kaggle.com/datasets/mahmoudreda55/satellite-image-classification) and extract it into the project directory.\n\n5. **Run the Jupyter Notebook**:\n\n   ```bash\n   jupyter notebook satellite.ipynb\n   ```\n\n   Follow the instructions in the notebook to train and evaluate the model.\n\n6. **For MATLAB users**:\n\n   Open `satellite_images.mlx` in MATLAB and run the script to train and evaluate the model.\n\n## Model Architecture\n\nThe CNN architecture includes:\n\n- Convolutional layers\n- Batch normalization\n- ReLU activation functions\n- Max pooling layers\n- Fully connected (dense) layers\n\n## Visualization\n\n```\n  _________________\n |      Input      |\n |      Data       |\n |_________________|\n         |\n  _________________\n |     Conv2D      |\n |_________________|\n |   BatchNorm2D   |\n |_________________|\n |      ReLU       |\n |_________________|\n |  MaxPooling2D   |\n |_________________|\n         |\n  _________________\n |     Conv2D      |\n |_________________|\n |   BatchNorm2D   |\n |_________________|\n |      ReLU       |\n |_________________|\n |  MaxPooling2D   |\n |_________________|\n         |\n  _________________\n |     Conv2D      |\n |_________________|\n |  BatchNorm2D    |\n |_________________|\n |      ReLU       |\n |_________________|\n |     Flatten     |\n |_________________|\n         |\n  _________________\n |      Dense      |\n |_________________|\n```\n\n\nThis structure is designed to effectively capture spatial hierarchies in the input images.\n\n## Results\n\nAfter training, the model achieves an accuracy of approximately 98% on the test set.\n\n## Contributing\n\nContributions are welcome. Feel free to open issues or submit pull requests.\n\n## License\n\nThis project is licensed under the MIT License. See the `LICENSE` file for details.\n\n## Acknowledgments\n\n- Dataset: [Kaggle: Satellite Image Classification](https://www.kaggle.com/datasets/mahmoudreda55/satellite-image-classification)\n\nFor any questions or suggestions, please contact [Christopher Aliu](https://github.com/al-chris). \n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fal-chris%2Fsatelliteimageclassification","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fal-chris%2Fsatelliteimageclassification","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fal-chris%2Fsatelliteimageclassification/lists"}