Generative Adversarial Networks in the built environment: A comprehensive review of the application of GANs across data types and scales
Abstract Generative Adversarial Networks (GANs) are a type of deep neural network that
have achieved many state-of-the-art results for generative tasks. GANs can be useful in the …
have achieved many state-of-the-art results for generative tasks. GANs can be useful in the …
Artificial intelligence studies in cartography: a review and synthesis of methods, applications, and ethics
The past decade has witnessed the rapid development of geospatial artificial intelligence
(GeoAI) primarily due to the ground-breaking achievements in deep learning and machine …
(GeoAI) primarily due to the ground-breaking achievements in deep learning and machine …
Deep learning for cross-domain data fusion in urban computing: Taxonomy, advances, and outlook
As cities continue to burgeon, Urban Computing emerges as a pivotal discipline for
sustainable development by harnessing the power of cross-domain data fusion from diverse …
sustainable development by harnessing the power of cross-domain data fusion from diverse …
GANmapper: geographical data translation
AN Wu, F Biljecki - International Journal of Geographical …, 2022 - Taylor & Francis
We present a new method to create spatial data using a generative adversarial network
(GAN). Our contribution uses coarse and widely available geospatial data to create maps of …
(GAN). Our contribution uses coarse and widely available geospatial data to create maps of …
Neural map style transfer exploration with GANs
S Christophe, S Mermet, M Laurent… - International Journal of …, 2022 - Taylor & Francis
ABSTRACT Neural Style Transfer is a Computer Vision topic intending to transfer the visual
appearance or the style of images to other images. Developments in deep learning nicely …
appearance or the style of images to other images. Developments in deep learning nicely …
Robotic instrument segmentation with image-to-image translation
E Colleoni, D Stoyanov - IEEE Robotics and Automation Letters, 2021 - ieeexplore.ieee.org
The semantic segmentation of robotic surgery video and the delineation of robotic
instruments are important for enabling automation. Despite major recent progresses, the …
instruments are important for enabling automation. Despite major recent progresses, the …
GAN-based satellite imaging: A survey on techniques and applications
H Mansourifar, A Moskovitz, B Klingensmith… - IEEE …, 2022 - ieeexplore.ieee.org
Satellite image analysis is widely used in many real-time applications, from agriculture to the
military. Due to the wide range of Generative Adversarial Network (GAN) applications in …
military. Due to the wide range of Generative Adversarial Network (GAN) applications in …
A Missing Traffic Data Imputation Method Based on a Diffusion Convolutional Neural Network–Generative Adversarial Network
C Zhang, L Zhou, X **ao, D Xu - Sensors, 2023 - mdpi.com
Traffic state data are key to the proper operation of intelligent transportation systems (ITS).
However, traffic detectors often receive environmental factors that cause missing values in …
However, traffic detectors often receive environmental factors that cause missing values in …
Representing vector geographic information as a tensor for deep learning based map generalisation
Recently, many researchers tried to generate (generalised) maps using deep learning, and
most of the proposed methods deal with deep neural network architecture choices. Deep …
most of the proposed methods deal with deep neural network architecture choices. Deep …
Predictability in human mobility: From individual to collective (vision paper)
Human mobility is the foundation of urban dynamics and its prediction significantly benefits
various downstream location-based services. Nowadays, while deep learning approaches …
various downstream location-based services. Nowadays, while deep learning approaches …