Fire

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Wildfire Prediction

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Wildfire Detection

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A Sentinel-2 benchmark dataset for deep-learning active-fire segmentation across 25 California wildfires
Sep 14, 2026Shreyan Mitra, Mohammadreza Narimani, Parastoo FarajpoorWildfire Detection Vision Datasets
Feature Recovery for Object Understanding After Irreversible Fire Damage
Sep 14, 2026Aditi Tiwari, Sofia Stoica, Savya Khosla +2Wildfire Detection Fine-Grained Perception
AI-Powered Flare Combustion Efficiency Estimation
Sep 12, 2026Afeefa Azam, Iyyakutti Iyappan Ganapathi, Fares Ossama Abdelhafez +5Turbofan Engines Methane
Multi-Agent Reinforcement Learning for Autonomous UAV Exploration in Wildfire Response
Sep 9, 2026Caden Chandra, Jerry NgWildfire Detection Multi-Agent Reinforcement Learning
D3ARC: Time-Critical Distributed Disaster Detection for Asynchronous Cooperative Multi-Robot Systems
Sep 7, 2026Nikolaos Koursioumpas, Lina Magoula, Nancy Alonistioti +1Wildfire Detection Multi-Robot Systems
Scale-based Approach for Active Wildfire Segmentation on Satellite Imagery
Sep 1, 2026Matheus F. Kovaleski, Cristiano Premebida, João Ruivo PauloWildfire Prediction Remote Sensing Image Segmentation
Multimodal RGB-Infrared Combination for UAV-Based Wildfire Segmentation: A Comparative Study on FLAME3
Sep 1, 2026Matheus F. Kovaleski, Luís Garrote, Cristiano Premebida +2Wildfire Detection Multi-Modal Fusion
FractalNet-Based Heterogeneous Federated Learning for Orbital Edge Intelligence in Satellite Mega-Constellations: A Wildfire Case Study
Sep 1, 2026Sai Puppala, Koushik SinhaFederated Learning Framework New Satellites
Random Forest-Informed Cellular Automaton for Large-Scale Wildfire Spread Modelling
Sep 1, 2026Siyu Chen, Esha Saha, Hao WangWildfire Prediction Random Forest
Evaluating AlphaEarth Foundations Embeddings for Wildfire Susceptibility Mapping
Aug 12, 2026Yuan Zhuang, Sanaa Hobeichi, Peng Shi +1Wildfire Prediction Wildfire Detection
FiRe: Fixed-Noise Refinement for Visual Counterfactual Explanations
Aug 9, 2026Yan Zeng, Changlu Guo, Oskar Kristoffersen +3Counterfactual Explanation Denoising Trajectory
Evaluating Machine Learning Models for Post-Wildfire Debris-Flow Prediction
Aug 5, 2026Quinn Ledingham, Zhengsen Xu, Yimin Zhu +6Wildfire Prediction Accurate Flood Prediction
Real-time physics inversion for retrieval of sub-pixel wildfire temperatures from VSWIR imaging spectroscopy
Aug 4, 2026William R. Keely, Philip G. Brodrick, Katherine Mistick +3Wildfire Prediction Thermal Imaging
Fighting Fire with Fire: On the Feasibility of Protecting Exercises Against AI Cheating
Aug 2, 2026Tobias Braun, Jonas Grebe, Louis Rethfeld +1Generative Artificial Intelligence Clickbait Detection
Impact of Dataset Composition on Embedded Real-Time UAV Wildfire Detection Using Compact YOLO Models
Aug 1, 2026Eduardo de los Santos, Andre S. Kelbouscas, Ricardo B. Grando +1Wildfire Detection Fire
Tensor Network Machine Learning for Wildfire Susceptibility Mapping: from Grokking Dynamics to Quantum Mixedness of Class Representations
Jul 21, 2026Domenico Pomarico, Alessandra Costantino, Gabriel Ramirez Sanchez +12Wildfire Prediction Tensor Networks
Spectral-Morphological Attention U-Net: An Efficient Network for Active Wildfire Detection
Jul 17, 2026Yugong Zeng, Jonathan WuWildfire Detection U-Net
Contextualized Early Detection of Online Firestorms: A Sequential LLM-Based Approach
Jul 16, 2026Besim Shala, Peter Mandl, Andreas Humpe +1Fire Discourse
LLMs Can See the Smoke but not the Fire: Evaluating Abductive Reasoning with Elenchos
Jul 14, 2026Julius Steiglechner, Lucas Mahler, Gabriele LohmannAbductive Reasoning Cryptographically Authorized Mutation
LTM: Large-scale Terrain Model for Wildfire-prone Landscapes
Jul 9, 2026Xiao Fu, Yue Hu, Meida Chen +2Wildfire Prediction Fire
Evaluating the Generalizability of Foundation Models for Extreme Environmental Events: Case Study of California Wildfire PM2.5
Jul 8, 2026Yongcan Huang, Li Jiang, Ze Yu LiuWildfire Prediction Time Series Foundation Models
Physics-guided spatiotemporal neural models for fuel density prediction
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Second MOASEI Competition at AAMAS'2026: A Technical Report
Jul 3, 2026Ceferino Patino, Tyler J. Billings, Alireza Saleh Abadi +4Decentralized Multi-Agent System Agentic Evaluations
DiPS: Dialogue Policy Selection for High-Stakes Persuasion Agents
Jul 2, 2026Tianyi Zhang, Mousumi Das, Abrar Anwar +2Persuasion Fire
FiRe: Frequency Reparameterization as a Preconditioner for Periodic Implicit Neural Representations
Jun 28, 2026Harinandan Shukla, Rajarshi Verma, Jitin SinglaImplicit Neural Representations Reparameterization
FlameVQA: A Physically-Grounded UAV Wildfire VQA Benchmark with Radiometric Thermal Supervision
Jun 25, 2026Mobin Habibpour, John Spodnik, Niloufar Alipour Talemi +1Wildfire Detection Textvqa
A Model-Driven Approach for Developing Families of Reinforcement Learning Environments
Jun 18, 2026Xiaoran Liu, Istvan DavidSafe Reinforcement Learning Environment
Neural Tree Reconstruction for the Open Forest Observatory
Jun 16, 2026Marissa Ramirez de Chanlatte, Arjun Rewari, Trevor Darrell +1Forest Biomass Neural Radiance Fields
ED3R: Energy-Aware Distributed Disaster Detection Enabled by Cooperative Robotic Agents
Jun 16, 2026Lina Magoula, Nikolaos Koursioumpas, Nancy Alonistioti +1Wildfire Detection Multi-Robot Systems
Spatio-Temporal Wildfire Spread Prediction in Canada using a Video Swin-Hybrid-U-Net and Satellite Imagery
Jun 15, 2026Maulik Srivastava, Esha Saha, Hao WangWildfire Prediction Satellite Imagery
HumP-KD: A Hybrid Uncertainty-Aware Multi-Stage Progressive Knowledge Distillation Framework for Efficient Fire Classification
Jun 12, 2026Mohammed Arif Mainuddin, Najifa Tabassum, Omar Ibne Shahid +1Heterogeneous Knowledge Distillation Fire
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Jun 12, 2026Ene Meco, Yingyi Luo, Emadeldeen Hamdan +2Wildfire Prediction U-Net
Aerial Wildfire Suppression Planning with a Hybrid CNN-Cellular Automata Fire Model
Jun 11, 2026Ion Matei, Maksym Zhenirovskyy, Takuya Kurihana +2Wildfire Prediction Fire
Neural-Parameterized Cellular Automata for Wildfire Spread
Jun 10, 2026Maksym Zhenirovskyy, Ion Matei, Rohit Vuppala +2Wildfire Prediction Neural Cellular Automata
A Large Scale Open-Source Image and Video Dataset for Robust Wildfire Detection and Classification
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Set Prediction for Next-Day Active Fire Forecasting
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On-Orbit Real-Time Wildfire Detection Under On-Board Constraints
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Low-Rank Adaptation of Geospatial Foundation Models for Wildfire Mapping Using Sentinel-2 Data
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WildFireVQA: A Large-Scale Radiometric Thermal VQA Benchmark for Aerial Wildfire Monitoring
Apr 22, 2026Mobin Habibpour, Niloufar Alipour Talemi, John Spodnik +2Wildfire Detection Fire
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Gaussians on Fire: High-Frequency Reconstruction of Flames
Nov 27, 2025Jakob Nazarenus, Dominik Michels, Wojtek Palubicki +43D Gaussian Fire
Machine Learning Guided Optimal Transmission Switching to Mitigate Wildfire Ignition Risk
Oct 29, 2025Weimin Huang, Ryan Piansky, Bistra Dilkina +1Ac Optimal Power Flow Fire
CanadaFireSat: Toward high-resolution wildfire forecasting with multiple modalities
Jun 10, 2025Hugo Porta, Emanuele Dalsasso, Jessica L. McCarty +1Wildfire Prediction Fire
FLAME 3 Dataset: Unleashing the Power of Radiometric Thermal UAV Imagery for Wildfire Management
Dec 3, 2024Bryce Hopkins, Leo ONeill, Michael Marinaccio +7Wildfire Detection Thermal Imaging

Sep 14, 2026 · eess.IVJ/K move · Enter open · S save

A Sentinel-2 benchmark dataset for deep-learning active-fire segmentation across 25 California wildfires

Shreyan Mitra, Mohammadreza Narimani, Parastoo Farajpoor

This article describes an open image dataset for developing and evaluating active-fire segmentation methods in satellite imagery. The dataset contains 2,148 image-mask pairs from 25 California wildfires, with acquisitions spanning July 2020 to August 2026. Each image is a 512x512-pixel, three-channel composite derived from Sentinel-2 Level-2A bands B12, B11 and B8A at 20 m spatial sampling. A fixed linear rendering is applied throughout the dataset. Corresponding masks distinguish background, SWIR-rule active fire and invalid observations. The masks were generated from shortwave-infrared brightness and near-infrared contrast, followed by constrained neighborhood growth. The release includes chip-level metadata and an incident-disjoint partition containing 18 training, three validation and four test fires. Among the image pairs, 841 contain active-fire labels; these labels occupy 0.0766% of all grid cells. A mask-blind analyst review covers 233 test chips and provides a separate assessment of the rule-generated labels at chip and connected-component levels. Reference training and evaluation code accompanies the data, including a ResNet-34 U-Net implementation with validation-based checkpoint and threshold selection. The archived images, masks, metadata and review annotations support research on rare-class segmentation, learning from algorithmic labels and transfer across fire incidents. The versioned dataset is deposited on Zenodo, with preparation and reuse software maintained in a public GitHub repository.

Wildfire Detection Vision Datasets

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