forest-fire-detection

Bu video bir proje tanıtım videosudur. Projede python programlama dilinde makine öğrenmesi (machine learning) ve görüntü işleme (computer vision OpenCV) kullanılarak orman yangınlarında eş zamanlı olarak duman ve ateş tespiti yapılmıştır.

A convolutional neural network(CNN) that detects forest fires.

AI/ML pipeline for next-day forest fire probability mapping & multi-hour spread simulation using VIIRS satellite data, Random Forest, and Cellular Automata at 30m resolution over Uttarakhand, India.

Automated Wildfire Prediction

Official implementation of LHRF-YOLO: A Lightweight Model with Hybrid Receptive Field for Forest Fire Detection (Forests 2025, 16, 1095). Built on Ultralytics YOLO.

This project aims to predict the occurrence of forest fires using machine learning. The project includes a Flask-based application that serves both backend (for model training and prediction) and frontend Created using Threejs (for user interaction).

Forest Fire-Smoke Detection and Classification

HMHCNN-mCBAM-for-Forest-Fire-Detection Hierarchical CNN with attention for aerial forest fire classification using UAV imagery.

A Python system that detects fire and smoke from live video or recorded footage, using computer vision techniques — no machine learning model or GPU required.

Forest fire detection over a LoRa sensor network. Six Raspberry Pis in a two-cluster multi-hop topology with TDMA scheduling, plus a 50-node browser simulator with LEACH clustering and GPSR routing.