{"id":28749360,"url":"https://github.com/drissiomar98/image-classification-cifar10","last_synced_at":"2026-04-24T23:31:38.597Z","repository":{"id":298390456,"uuid":"994406214","full_name":"drissiOmar98/Image-classification-CIFAR10","owner":"drissiOmar98","description":"A deep learning project comparing ANN and CNN architectures for classifying 32×32 color images across 10 categories in the CIFAR-10 dataset.","archived":false,"fork":false,"pushed_at":"2025-06-10T21:05:56.000Z","size":351,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":0,"default_branch":"master","last_synced_at":"2025-06-10T22:20:43.392Z","etag":null,"topics":["cnn-classification","deep-learning","keras-tensorflow","tensorflow"],"latest_commit_sha":null,"homepage":"","language":"Jupyter 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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-classification","deep-learning","keras-tensorflow","tensorflow"],"created_at":"2025-06-16T20:08:47.857Z","updated_at":"2026-04-24T23:31:38.583Z","avatar_url":"https://github.com/drissiOmar98.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"# CIFAR-10 Image Classification with Deep Learning\n\n[![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT)\n[![Python 3.8+](https://img.shields.io/badge/Python-3.8%2B-blue.svg)](https://www.python.org/downloads/)\n[![TensorFlow 2.12+](https://img.shields.io/badge/TensorFlow-2.12+-FF6F00?logo=tensorflow)](https://www.tensorflow.org/)\n[![Keras](https://img.shields.io/badge/Keras-D00000?logo=keras\u0026logoColor=white)](https://keras.io/)\n[![OpenCV](https://img.shields.io/badge/OpenCV-5C3EE8?logo=opencv\u0026logoColor=white)](https://opencv.org/)\n[![scikit-learn](https://img.shields.io/badge/scikit--learn-F7931E?logo=scikit-learn\u0026logoColor=white)](https://scikit-learn.org/)\n[![Jupyter](https://img.shields.io/badge/Jupyter-F37626?logo=jupyter\u0026logoColor=white)](https://jupyter.org/)\n[![NumPy](https://img.shields.io/badge/Numpy-013243?logo=numpy\u0026logoColor=white)](https://numpy.org/)\n[![Pandas](https://img.shields.io/badge/Pandas-150458?logo=pandas\u0026logoColor=white)](https://pandas.pydata.org/)\n[![Matplotlib](https://img.shields.io/badge/Matplotlib-11557C?logo=python\u0026logoColor=white)](https://matplotlib.org/)\n[![Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/your-username/cifar10-classification/blob/main/CIFAR10_Classification.ipynb)\n\nA deep learning project comparing ANN and CNN architectures for classifying 32×32 color images across 10 categories in the CIFAR-10 dataset.\n\n## Table of Contents\n- [Overview](#overview)\n- [Key Features](#key-features)\n- [Technologies Used](#technologies-used)\n- [Results](#results)\n- [Installation](#installation)\n\n\n## Overview\nThis project implements and compares two approaches for image classification:\n\n- **Artificial Neural Network (ANN)**: Baseline fully-connected model\n- **Convolutional Neural Network (CNN)**: Advanced architecture featuring:\n  - Convolutional layers with ReLU activation\n  - Batch normalization\n  - Dropout regularization (30-50%)\n  - Data augmentation pipeline\n  - L2 weight regularization\n\nThe CIFAR-10 dataset contains 50,000 training and 10,000 test images across 10 object categories.\n\n## Key Features\n✔️ Comprehensive ANN vs CNN performance comparison  \n✔️ Advanced data augmentation pipeline  \n✔️ Real-time training visualization  \n✔️ Detailed classification metrics (precision/recall/F1)  \n✔️ Confusion matrix analysis  \n✔️ Regularization suite (Dropout, BatchNorm, L2)  \n✔️ Early stopping with model checkpointing  \n\n## Technologies Used\n\n### Core Frameworks\n| Technology | Purpose | Version |\n|------------|---------|---------|\n| ![TensorFlow](https://img.shields.io/badge/TensorFlow-FF6F00?logo=tensorflow\u0026logoColor=white) | Deep learning framework | 2.12+ |\n| ![Keras](https://img.shields.io/badge/Keras-D00000?logo=keras\u0026logoColor=white) | High-level API | Built-in |\n| ![Scikit-learn](https://img.shields.io/badge/scikit--learn-F7931E?logo=scikit-learn\u0026logoColor=white) | Model evaluation | 1.2+ |\n\n### Data Processing\n| Technology | Purpose |\n|------------|---------|\n| ![NumPy](https://img.shields.io/badge/Numpy-013243?logo=numpy\u0026logoColor=white) | Array operations |\n| ![Pandas](https://img.shields.io/badge/Pandas-150458?logo=pandas\u0026logoColor=white) | Data analysis |\n\n### Visualization\n| Technology | Purpose |\n|------------|---------|\n| ![Matplotlib](https://img.shields.io/badge/Matplotlib-11557C?logo=python\u0026logoColor=white) | Training plots |\n| ![Seaborn](https://img.shields.io/badge/Seaborn-4C72B0?logo=python\u0026logoColor=white) | Statistical visuals |\n\n### Model Optimization\n| Technology | Purpose |\n|------------|---------|\n| ![ImageDataGenerator](https://img.shields.io/badge/Keras_Augmentation-5C3EE8) | Real-time augmentation |\n| ![EarlyStopping](https://img.shields.io/badge/Keras_Callbacks-D00000) | Prevent overfitting |\n\n## Results\n\n### Performance Comparison\n| Model | Train Accuracy | Test Accuracy | Parameters|\n|-------|----------------|---------------|------------|\n| ANN   | 49.4%          | 46.2%         | 820,874 |\n| CNN   | **73.2%**      | **72.4%**     |  1,253,674 |\n\n\n\n## Installation\n```bash\n# Clone repository\ngit clone https://github.com/drissiOmar98/Image-classification-CIFAR10.git\ncd Image-classification-CIFAR10\n\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fdrissiomar98%2Fimage-classification-cifar10","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fdrissiomar98%2Fimage-classification-cifar10","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fdrissiomar98%2Fimage-classification-cifar10/lists"}