A Diffusion Model-Generated Forest Fire Dataset

Published: 4 December 2024| Version 1 | DOI: 10.17632/nwzcm9ckrt.1
Contributors:
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,
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, Sharia Arfin Tanim,

Description

This dataset consists of 2,204 AI-generated images, created using a Stable Diffusion model. The images are organized into two distinct folders: Fire: Contains 1,102 images depicting synthetic representations of forest fires. Non-Fire: Contains 1,102 images showing various forest scenes without any fire activity. Each image has a resolution of 150x150 pixels, optimized for use in machine learning tasks such as classification, detection, and environmental monitoring. Purpose The dataset is intended to aid research and development in areas such as: Forest fire detection and prevention using AI. Benchmarking deep learning models for image classification tasks. Studying the environmental impact of forest fires. Key Features Generated with Stable Diffusion, ensuring high-quality and varied synthetic visuals. Balanced dataset structure (equal representation of fire and non-fire images). Small image size (150x150), suitable for lightweight model training and testing.

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Institutions

Multimedia University, American International University Bangladesh, East Delta University

Categories

Object Detection, Image Classification

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