A survey on generative adversarial networks: Variants, applications, and training
The Generative Models have gained considerable attention in unsupervised learning via a
new and practical framework called Generative Adversarial Networks (GAN) due to their …
new and practical framework called Generative Adversarial Networks (GAN) due to their …
How good is my GAN?
K Shmelkov, C Schmid… - Proceedings of the …, 2018 - openaccess.thecvf.com
Generative adverserial networks (GANs) are one of the most popular methods for generating
images today. While impressive results have been validated by visual inspection, a number …
images today. While impressive results have been validated by visual inspection, a number …
Real-time detection and forecast of flashovers by the visual room fire features using deep convolutional neural networks
Flashover occurs in building fires whereby all the combustible materials in an enclosure
begin to ignite rapidly. This detrimental phenomenon occurs because of the intense heat …
begin to ignite rapidly. This detrimental phenomenon occurs because of the intense heat …
A review of modelling and simulation methods for flashover prediction in confined space fires
Confined space fires are common emergencies in our society. Enclosure size, ventilation, or
type and quantity of fuel involved are factors that determine the fire evolution in these …
type and quantity of fuel involved are factors that determine the fire evolution in these …
Deep learning based inverse model for building fire source location and intensity estimation
Effective fire detection provides early warnings and key information for first responders and
people trapped insides. The idea of integrating sensor data and fire modeling presents a …
people trapped insides. The idea of integrating sensor data and fire modeling presents a …
Real-time flashover prediction model for multi-compartment building structures using attention based recurrent neural networks
This paper presents the development of an attention based bi-directional gated recurrent
unit model, P-Flashv2, for the prediction of potential occurrence of flashover in a traditional …
unit model, P-Flashv2, for the prediction of potential occurrence of flashover in a traditional …
Deep neural networks for pattern recognition
In the field of pattern recognition research, the method of using deep neural networks based
on improved computing hardware recently attracted attention because of their superior …
on improved computing hardware recently attracted attention because of their superior …
A feasibility study on translation of RGB images to thermal images: Development of a machine learning algorithm
The thermal image is an important source of data in the fire safety research area, as it
provides temperature information at pixel-level of a region. The combination of temperature …
provides temperature information at pixel-level of a region. The combination of temperature …
Small target detection for search and rescue operations using distributed deep learning and synthetic data generation
It is important to find the target as soon as possible for search and rescue operations.
Surveillance camera systems and unmanned aerial vehicles (UAVs) are used to support …
Surveillance camera systems and unmanned aerial vehicles (UAVs) are used to support …
Improved visible to IR image transformation using synthetic data augmentation with cycle-consistent adversarial networks
K Yun, K Yu, J Osborne, S Eldin… - … and Tracking XXX, 2019 - spiedigitallibrary.org
Infrared (IR) images are essential to improve the visibility of dark or camouflaged objects.
Object recognition and segmentation based on a neural network using IR images provide …
Object recognition and segmentation based on a neural network using IR images provide …