{"id":50961356,"url":"https://github.com/bennourines/pneumonia-detection-cnn","last_synced_at":"2026-06-18T14:31:55.825Z","repository":{"id":323773782,"uuid":"1094644258","full_name":"bennourines/pneumonia-detection-cnn","owner":"bennourines","description":"CNN model for pneumonia detection from chest X-ray images, fine-tuned with ResNet50 and achieving 94% accuracy on ChestX-ray dataset.","archived":false,"fork":false,"pushed_at":"2025-11-12T01:41:32.000Z","size":3483,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":0,"default_branch":"main","last_synced_at":"2025-11-12T03:19:58.248Z","etag":null,"topics":["cnn","computer-vision","deep-learning","image-classification","machine-learning","resnet-50","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":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/bennourines.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":null,"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":"2025-11-12T01:37:33.000Z","updated_at":"2025-11-12T01:46:55.000Z","dependencies_parsed_at":null,"dependency_job_id":null,"html_url":"https://github.com/bennourines/pneumonia-detection-cnn","commit_stats":null,"previous_names":["bennourines/pneumonia-detection-cnn"],"tags_count":null,"template":false,"template_full_name":null,"purl":"pkg:github/bennourines/pneumonia-detection-cnn","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/bennourines%2Fpneumonia-detection-cnn","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/bennourines%2Fpneumonia-detection-cnn/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/bennourines%2Fpneumonia-detection-cnn/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/bennourines%2Fpneumonia-detection-cnn/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/bennourines","download_url":"https://codeload.github.com/bennourines/pneumonia-detection-cnn/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/bennourines%2Fpneumonia-detection-cnn/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":34495377,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-05-26T15:22:16.424Z","status":"online","status_checked_at":"2026-06-18T02:00:06.871Z","response_time":128,"last_error":null,"robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":true,"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","computer-vision","deep-learning","image-classification","machine-learning","resnet-50","tensorflow"],"created_at":"2026-06-18T14:31:55.059Z","updated_at":"2026-06-18T14:31:55.813Z","avatar_url":"https://github.com/bennourines.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"# 🩺 Pneumonia Detection from Chest X-Ray Images\n\n### 🎓 Project — ESPRIT (2024)\n**Author:** Inès Bennour  \n**Institution:** ESPRIT, Tunisia  \n**Year:** 2024  \n\n---\n\n## 🧠 Project Overview\n\nThis project focuses on building a **Convolutional Neural Network (CNN)** for the **automatic detection of pneumonia** from chest X-ray images.  \nThe goal is to assist radiologists in early diagnosis by leveraging **deep learning** and **computer vision**.\n\n---\n\n## 🚀 Objectives\n\n- Design a CNN architecture capable of classifying X-ray images into **Pneumonia** vs **Normal**.\n- Enhance model performance through:\n  - **Data Augmentation**\n  - **Fine-tuning of the ResNet50** pre-trained model.\n- Achieve high diagnostic accuracy on real-world medical data.\n\n---\n\n## 🧩 Dataset\n\n- **Dataset Used:** [ChestX-ray Pneumonia Dataset (Kaggle)](https://www.kaggle.com/datasets/paultimothymooney/chest-xray-pneumonia)\n- **Classes:**  \n  - `PNEUMONIA`  \n  - `NORMAL`\n- **Dataset Split:**  \n  - 70% training  \n  - 20% validation  \n  - 10% testing  \n\n---\n\n## 🏗️ Model Architecture\n\n### 1️⃣ Baseline CNN\n- Custom CNN with convolutional + pooling layers.\n- Activation: ReLU  \n- Optimizer: Adam  \n- Loss: Binary Crossentropy  \n\n### 2️⃣ Fine-Tuned ResNet50\n- Pre-trained on **ImageNet**.\n- Top layers replaced with custom dense layers.\n- Data augmentation applied (rotation, zoom, horizontal flip).\n- Fine-tuning performed on last layers for optimal performance.\n\n---\n\n## 📊 Results\n\n| Model                | Accuracy | Precision | Recall | F1-Score |\n|----------------------|-----------|------------|--------|-----------|\n| Baseline CNN         | 87%       | 85%        | 88%    | 86%       |\n| **ResNet50 (Fine-Tuned)** | **94%** | **93%** | **95%** | **94%** |\n\n✅ **Final Model Accuracy: 94%**\n\n---\n\n## 🛠️ Technologies \u0026 Tools\n\n- **Python**\n- **TensorFlow / Keras**\n- **OpenCV**\n- **Matplotlib / Seaborn**\n- **NumPy / Pandas**\n- **Jupyter Notebook**\n\n---\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fbennourines%2Fpneumonia-detection-cnn","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fbennourines%2Fpneumonia-detection-cnn","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fbennourines%2Fpneumonia-detection-cnn/lists"}