[HTML][HTML] Integration of convolutional and adversarial networks into building design: A review
Convolutional and adversarial networks are found in various fields of knowledge and
activities. One such field is building design, a multi-disciplinary and multi-task process …
activities. One such field is building design, a multi-disciplinary and multi-task process …
[HTML][HTML] Crossgeonet: A framework for building footprint generation of label-scarce geographical regions
Building footprints are essential for understanding urban dynamics. Planet satellite imagery
with daily repetition frequency and high resolution has opened new opportunities for …
with daily repetition frequency and high resolution has opened new opportunities for …
Towards scalable economic photovoltaic potential analysis using aerial images and deep learning
Roof-mounted photovoltaic systems play a critical role in the global transition to renewable
energy generation. An analysis of roof photovoltaic potential is an important tool for …
energy generation. An analysis of roof photovoltaic potential is an important tool for …
[HTML][HTML] Identification of undocumented buildings in cadastral data using remote sensing: Construction period, morphology, and landscape
Buildings are the predominant objects that characterize the urban structure. For many cities,
local governments establish building databases for administration as well as urban planning …
local governments establish building databases for administration as well as urban planning …
Diminished reality using semantic segmentation and generative adversarial network for landscape assessment: evaluation of image inpainting according to colour …
The objective of this research is to develop a method to detect and virtually remove
representations of existing buildings from a video stream in real-time for the purpose of …
representations of existing buildings from a video stream in real-time for the purpose of …
Urban sprawl and covid-19 impact analysis by integrating deep learning with google earth engine
Timely information on land use, vegetation coverage, and air and water quality, are crucial
for monitoring and managing territories, especially for areas in which there is dynamic urban …
for monitoring and managing territories, especially for areas in which there is dynamic urban …
Multimodal Co-learning for Building Change Detection: A Domain Adaptation Framework Using VHR Images and Digital Surface Models
In this article, we propose a multimodal co-learning framework for building change detection.
This framework can be adopted to jointly train a Siamese bitemporal image network and a …
This framework can be adopted to jointly train a Siamese bitemporal image network and a …
Sci-Net: scale-invariant model for buildings segmentation from aerial imagery
H Nasrallah, M Shukor, AJ Ghandour - Signal, Image and Video …, 2023 - Springer
Buildings' segmentation is a fundamental task in the field of earth observation and aerial
imagery analysis. Most existing deep learning-based methods in the literature can be …
imagery analysis. Most existing deep learning-based methods in the literature can be …
ChangeDA: Depth-Augmented Multi-task Network for Remote Sensing Change Detection via Differential Analysis
J Meng, X Xu, Z Zhang, P Li, G **e… - IEEE Transactions on …, 2025 - ieeexplore.ieee.org
In the field of Remote Sensing Change Detection (RSCD), accurately identifying significant
changes between bitemporal images is essential for environmental monitoring, urban …
changes between bitemporal images is essential for environmental monitoring, urban …
[PDF][PDF] Automatic diminished reality-based virtual demolition method using semantic segmentation and generative adversarial network for landscape assessment
In redevelopment projects in mature cities, it is important to visualize the future landscape.
Diminished reality (DR) based methods have been proposed to represent the future …
Diminished reality (DR) based methods have been proposed to represent the future …