Tackling climate change with machine learning
Climate change is one of the greatest challenges facing humanity, and we, as machine
learning (ML) experts, may wonder how we can help. Here we describe how ML can be a …
learning (ML) experts, may wonder how we can help. Here we describe how ML can be a …
OpenStreetMap: Challenges and opportunities in machine learning and remote sensing
OpenStreetMap (OSM) is a community-based, freely available, editable map service created
as an alternative to authoritative sources. Given that it is edited mainly by volunteers with …
as an alternative to authoritative sources. Given that it is edited mainly by volunteers with …
Lane-level street map extraction from aerial imagery
S He, H Balakrishnan - … of the IEEE/CVF Winter Conference …, 2022 - openaccess.thecvf.com
Digital maps with lane-level details are the foundation of many applications. However,
creating and maintaining digital maps especially maps with lane-level details, are labor …
creating and maintaining digital maps especially maps with lane-level details, are labor …
Beyond geo-localization: Fine-grained orientation of street-view images by cross-view matching with satellite imagery
Street-view imagery provides us with novel experiences to explore different places remotely.
Carefully calibrated street-view images (eg, Google Street View) can be used for different …
Carefully calibrated street-view images (eg, Google Street View) can be used for different …
Towards scalable economic photovoltaic potential analysis using aerial images and deep learning
S Krapf, N Kemmerzell, S Khawaja Haseeb Uddin… - Energies, 2021 - mdpi.com
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 …
Multimodal deep learning for robust road attribute detection
Automatic inference of missing road attributes (eg, road type and speed limit) for enriching
digital maps has attracted significant research attention in recent years. A number of …
digital maps has attracted significant research attention in recent years. A number of …
Beyond road extraction: A dataset for map update using aerial images
The increasing availability of satellite and aerial imagery has sparked substantial interest in
automatically updating street maps by processing aerial images. Until now, the community …
automatically updating street maps by processing aerial images. Until now, the community …
Beecluster: drone orchestration via predictive optimization
The rapid development of small aerial drones has enabled numerous drone-based
applications, eg, geographic mapping, air pollution sensing, and search and rescue. To …
applications, eg, geographic mapping, air pollution sensing, and search and rescue. To …
Centaur VGI: An evaluation of engagement, speed, and quality in hybrid humanitarian mapping
Volunteered geographic information (VGI) is often cited as a potential solution to persistent
global inequalities in map data, particularly in areas undergoing humanitarian crises. Poor …
global inequalities in map data, particularly in areas undergoing humanitarian crises. Poor …
A general framework for human-machine digitization of geographic regions from remotely sensed imagery
CJ Michael, SM Dennis, C Maryan, S Irving… - Proceedings of the 27th …, 2019 - dl.acm.org
Digitization of geographic regions, such as bodies of water, from remotely sensed imagery is
a highly demanded yet arduous task. Though many automatic approaches for such …
a highly demanded yet arduous task. Though many automatic approaches for such …