real-time fire detection in video imagery using a convolutional neural network (deep learning) - from our ICIP 2018 paper (Dunnings / Breckon) + ICMLA 2019 paper (Samarth / Bhowmik / Breckon)
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Updated
Jul 22, 2021 - Python
real-time fire detection in video imagery using a convolutional neural network (deep learning) - from our ICIP 2018 paper (Dunnings / Breckon) + ICMLA 2019 paper (Samarth / Bhowmik / Breckon)
D-Fire: an image data set for fire and smoke detection.
Fire and Gun detection using yolov3 in videos as well as images. Training code, dataset and trained weight file available.
Real-time fire detection in image/video/webcam using a convolutional neural network (deep learning) - from our ICMLA 2020 paper (Thomson / Bhowmik / Breckon)
Fire and smoke detection using spatial and temporal patterns.
This repository showcases our work on using computer vision to detect wildfires. Explore the code, model, and results of our research on wildfire prevention.
Fire-Detection-using-YOLOv8
Deep Learning model implementation for Fire detection both classification and segmentation from the FLAME dataset.
Deep Learning-Based Fire Vehicle Detection and Real-Time Warning System 基於深度學習的火災車輛偵測及即時預警系統
This is the YoloV5 fire detection application.
Robot that explores a building while mapping and detecting fire hazards and survivors
Fire Detection System Using Gas and Temperature Sensors
This is an implementation of the floodfill algorithm for fire event detection as described in Archibald & Roy 2009. For docs see:
In this project, we developed a Raspberry Pi-based robotic car equipped with a Pi Camera for fire detection as well as for live video feed. The car can be controlled remotely by the user through WiFi. Additionally, it gathers temperature and humidity data, sending it to a Google spreadsheet hosted in Google Drive for storage and analysis.
API endpoint which takes images as input, and tries to detect and classify the presence of smoke and fire
Fire detection using satellite imagery, project for Digital image processing and analysis course @ University of Zagreb, Faculty of Electrical Engineering and Computing
Final work featuring data collection, training and testing of YOLOv8 fire detection model and its deployment using Streamlit
Fire detection with AI and instant multi-functional response system.
This repository showcases our work on using computer vision to detect wildfires. Explore the code, model, and results of our research on wildfire prevention.
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