Welcome to 100 Computer Vision Notebooks — a personal exploring a wide range of Computer Vision techniques. This repository is part of my journey as a Computer Science passionate about real-world applications of deep learning, image processing, and explainable AI.
Whether you're a beginner looking to learn or a researcher exploring practical implementations, you'll find value in these diverse, hands-on projects.
The goal of this repository is to:
- ✅ Build 100 practical, computer vision notebooks
- ✅ Cover a wide variety of domains (medical imaging, agriculture, natural images, etc.)
- ✅ Apply both classic and modern deep learning models
- ✅ Incorporate Explainable AI (XAI) techniques like SHAP, LIME, Grad-CAM
- ✅ Foster open collaboration and community contribution
Here’s a brief look at what's currently included:
| # | Project Title |
|---|---|
| 1 | Digit Recognition (MNIST) |
| 2 | Face Detection |
| 3 | Skin Cancer Classification using Xception |
| 4 | Chest X-Ray Image Analysis |
| 5 | Forward and Inverse Network |
| 6 | Y-Net for Segmentation |
| 7 | Eye Diseases Classification |
| 8 | Wheat Plant Disease Detection |
| 9 | Nitrogen Deficiency & Leaf Rust Detection |
| 10 | Image Colorization with Autoencoder |
| 11 | XAI (SHAP & LIME) for Plant Pathogen Classification |
| 12 | Conv2D vs SeparableConv2D Analysis |
| 13 | Denoising Autoencoder |
| 14 | Autoencoders with Dense & Convolutional Layers |
| 15 | CNN for Fungi Microscopic Image Classification |
| 16 | SHAP, LIME, Grad-CAM for Fungi Classification |
| 17 | XAI Techniques for Fungi Classification |
| 18 | Rice Leaf Disease Detection |
| 19 | Leaf Detection using YOLO |
| 20 | General Image Processing Techniques |
🔄 This list is growing every week! Expect cutting-edge notebooks involving object detection, vision transformers, medical imaging segmentation, etc. models in upcoming commits.
- Python
- TensorFlow / Keras
- PyTorch
- OpenCV
- Matplotlib / Seaborn
- Scikit-learn
- XAI Libraries: SHAP, LIME, Grad-CAM
👉 https://www.kaggle.com/mdismielhossenabir
✅ 20/100 notebooks complete
⏳ 80 to go!
I will continue updating this repository until all 100 notebooks are committed. Stay tuned!