AbdullahImran/DeepLearningProject

Deep Learning Project

Dataset Summary

This repository contains the datasets, trained models, notebooks, experiments, feature-extraction outputs, and supporting resources developed for a deep learning project focused on fire detection, fire severity classification, and related computer vision tasks.

The project covers multiple stages of a deep learning workflow, including binary fire classification, three-class fire severity classification, feature extraction, dimensionality reduction, clustering, and recommendation generation.

The repository contains approximately 2.1 GB of files across 1,700+ files.

Dataset Details

Dataset Description

The repository is a collection of datasets and machine-learning artifacts rather than a single standardized dataset. It contains resources used across multiple deep learning experiments and application components.

The main components include:

• Fire vs. No-Fire binary image classification
• Three-class fire severity classification
• Feature extraction
• Severity clustering
• Dimensionality reduction
• Recommendation generation
• Generated severity-image samples
• Jupyter notebooks
• Trained models and model checkpoints
• Supporting application resources

Main Project Components

Fire vs. No-Fire Binary Classification

Fire_vs_No_Fire_Binary_Classification/

Contains resources for binary image classification between:

• Fire
• No Fire

The project includes experiments using:

• ResNet50
• Custom CNN
• VGG16
• EfficientNetB0

The directory also contains a dataset, trained model resources, and VGG16 checkpoints.

Fire Severity Detection

Severity_Detection_Tri_Classification/

Contains resources for three-class fire severity classification:

• Mild
• Moderate
• Severe

The project includes experiments using:

• Xception
• EfficientNetB0

Additional components include feature extraction, clustering, dimensionality reduction, and dataset preparation.

Severity Dataset

Severity_Detection_Tri_Classification/Severity_Altered_Dataset/

Contains an image dataset organized into training, validation, and testing splits.

severity_dataset/
├── train/
│   ├── mild/
│   ├── moderate/
│   └── severe/
├── val/
│   ├── mild/
│   ├── moderate/
│   └── severe/
└── test/
    ├── mild/
    ├── moderate/
    └── severe/