Early fire detection using convolutional neural networks during surveillance for effective disaster management. Proposed a framework, which avoids the tedious and time-consuming process …

We show the relative performance achieved against prior work using benchmark datasets to illustrate maximally robust real-time fire region detection." (1) using InceptionV1-OnFire CNN …

Jun 1, 2020 · To improve the performance of image fire detection technology, the advanced object detection CNNs of Faster-RCNN, R–FCN, SSD, and YOLO v3 are used to develop …

Dec 24, 2021 · The CNN method was used to detect the fire in the images. The CNN model was trained with the transfer learning method using the Inception V3, SequeezeNet, VGG16 and …

Dec 11, 2023 · Based on Convolutional Neural Network (CNN) technology, this research provides a novel fire detection system. By researching fire flame features and utilising edge detection …

enhanced fire detection framework using a CNN-based model, with a focus on higher accuracy, faster inference, and better performance in a range of environmental situations.

To overcome these limitations, vision-based real-time fire detection has been enabled in surveillance devices. Once fire appears in any camera, the approach can detect it and send a …

Sep 1, 2023 · In this work, we identify the requirements and the constraints in terms of computational resources of this workflow, and investigate lightweight CNNs to be used. …

In this study, we offer an innovative, energy-efficient, and computationally effective CNN model for detection of fire, localization, and understanding of the fire scenario, based on the SqueezeNet …

To develop a classification model that uses Deep Learning to recognize fires in images/video frames, allowing for early detection and reducing manual work. In surveillance videos, this …