arXiv Computer Vision September 11, 2026 By Afeefa Azam, Iyyakutti Iyappan Ganapathi, Fares Ossama Abdelhafez, Divya Velayudhan, Maregu Assefa Habtie, Hamad Karki, Khalid Yousef Al Awadhi, Naoufel Werghi

AI-Powered Flare Combustion Efficiency Estimation

Read the original on arXiv Computer Vision →

The paper presents a lightweight vision‑language encoder paired with a compact multi‑layer perceptron to estimate flare combustion efficiency from low‑cost thermal video. The trained model is deployed via a user‑friendly GUI that overlays efficiency values on each frame, tracks real‑time trends, visualizes distribution across the video, and exports CSV reports. In a six‑month trial, the system maintained 99% uptime with under 15 minutes of weekly maintenance.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv Computer Vision.

multimodal

arXiv AI

Jul 9

Physics-guided spatiotemporal neural models for fuel density prediction

arXiv:2607. 06999v1 Announce Type: cross Abstract: This paper presents a physics-guided machine learning (PGML) framework for fuel density prediction, integrating physics constraints and domain knowledge into deep learning models to enhance model accuracy and stability.

By Tolga Caglar, Jaynil Jaiswal, Saqib Azim, Yudhir Gala, Mai H. Nguyen, Ilkay Altintas

llms computer-vision

arXiv Machine Learning

Jun 8

Video-Based Prediction of In-Flight Particle Characteristics in Atmospheric Plasma Spraying

arXiv:2606. 07416v1 Announce Type: new Abstract: Atmospheric plasma spraying (APS) is a widely used coating process in which in-flight particle temperature and velocity strongly influence coating quality.

By Abhijeet Praveen, Sareh Soleimani, Cormac Cureton, Aman Sidhu, Kintak Raymond Yu, Cristian Cojocaru, Narges Armanfard

arXiv Computer Vision

2d ago

A Large Scale Open-Source Image and Video Dataset for Robust Wildfire Detection and Classification

arXiv:2606.10174v2 Announce Type: replace Abstract: Wildfire detection and monitoring are critical for mitigating fire spread and reducing environmental and infrastructural damage. In this work, we i...

By Emadeldeen Hamdan, Yingyi Luo, B. Ugur Toreyin, Erdem Koyuncu, Adam J. Watts, Ugur Gudukbay, Ahmet Enis Cetin

llms benchmarks

arXiv AI

Jun 30

FLAME 3 Dataset: Unleashing the Power of Radiometric Thermal UAV Imagery for Wildfire Management

arXiv:2412. 02831v2 Announce Type: replace-cross Abstract: The increasing accessibility of radiometric thermal imaging sensors for unmanned aerial vehicles (UAVs) offers significant potential for advancing AI-driven aerial wildfire management.

By Bryce Hopkins, Leo ONeill, Michael Marinaccio, Mobin Habibpour, Eric Rowell, Russell Parsons, Sarah Flanary, Irtija Nazim, Carl Seielstad, Fatemeh Afghah

computer-vision

arXiv Computer Vision

Sep 1

JVLGS: Joint Vision-Language Gas Leak Segmentation

arXiv:2508.19485v2 Announce Type: replace Abstract: Gas leaks pose severe risks to human health and industrial safety. However, accurate and timely monitoring of gas leaks remains a major challenge....

By Xinlong Zhao, Qixiang Pang, Shan Du

computer-vision multimodal benchmarks safety

arXiv Machine Learning

Jul 23

A Deep Learning Framework for Predicting Solar EUV Irradiance During Significant Flares

arXiv:2607. 19597v1 Announce Type: cross Abstract: We present FlareEUV, a multimodal deep learning framework for predicting daily extreme ultraviolet (EUV) irradiance at 6.

By Sathvik Soman, Jason T. L. Wang, Haimin Wang, Haodi Jiang

multimodal