Anthony Ortiz
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View article: AI-Enabled Screening for Retinopathy of Prematurity in Low-Resource Settings
AI-Enabled Screening for Retinopathy of Prematurity in Low-Resource Settings Open
Importance Retinopathy of prematurity (ROP) is the leading cause of preventable childhood blindness worldwide. If detected and treated early, ROP-associated blindness is preventable; however, identifying patients who might respond to treat…
View article: Global Renewables Watch: A Temporal Dataset of Solar and Wind Energy Derived from Satellite Imagery
Global Renewables Watch: A Temporal Dataset of Solar and Wind Energy Derived from Satellite Imagery Open
We present a comprehensive global temporal dataset of commercial solar photovoltaic (PV) farms and onshore wind turbines, derived from high-resolution satellite imagery analyzed quarterly from the fourth quarter of 2017 to the second quart…
View article: FLAVARS: A Multimodal Foundational Language and Vision Alignment Model for Remote Sensing
FLAVARS: A Multimodal Foundational Language and Vision Alignment Model for Remote Sensing Open
Remote sensing imagery is dense with objects and contextual visual information. There is a recent trend to combine paired satellite images and text captions for pretraining performant encoders for downstream tasks. However, while contrasti…
View article: TorchGeo: Deep Learning With Geospatial Data
TorchGeo: Deep Learning With Geospatial Data Open
Remotely sensed geospatial data are critical for applications including precision agriculture, urban planning, disaster monitoring and response, and climate change research, among others. Deep learning methods are particularly promising fo…
View article: PGRID: Power Grid Reconstruction in Informal Developments Using High-Resolution Aerial Imagery
PGRID: Power Grid Reconstruction in Informal Developments Using High-Resolution Aerial Imagery Open
As of 2023, a record 117 million people have been displaced worldwide, more than double the number from a decade ago [22]. Of these, 32 million are refugees under the UNHCR mandate, with 8.7 million residing in refugee camps. A critical is…
View article: Land use and Europe’s renewable energy transition: identifying low-conflict areas for wind and solar development
Land use and Europe’s renewable energy transition: identifying low-conflict areas for wind and solar development Open
Continued dependence on imported fossil fuels is rapidly becoming unsustainable in the face of the twin challenges of global climate change and energy security demands in Europe. Here we present scenarios in line with REPowerEU package to …
View article: A Change Detection Reality Check
A Change Detection Reality Check Open
In recent years, there has been an explosion of proposed change detection deep learning architectures in the remote sensing literature. These approaches claim to offer state-of-the-art performance on different standard benchmark datasets. …
View article: Seeing the roads through the trees: A benchmark for modeling spatial dependencies with aerial imagery
Seeing the roads through the trees: A benchmark for modeling spatial dependencies with aerial imagery Open
Fully understanding a complex high-resolution satellite or aerial imagery scene often requires spatial reasoning over a broad relevant context. The human object recognition system is able to understand object in a scene over a long-range r…
View article: The Road to India’s Renewable Energy Transition Must Pass through Crowded Lands
The Road to India’s Renewable Energy Transition Must Pass through Crowded Lands Open
The significance of renewable energy in achieving necessary reductions in emissions to limit global warming to 1.5 degrees Celsius is widely acknowledged. However, there is growing concern over the allocation of land for constructing the r…
View article: Efficacy of the spatial repellent product Mosquito Shield™ against wild pyrethroid-resistant Anopheles arabiensis in south-eastern Tanzania
Efficacy of the spatial repellent product Mosquito Shield™ against wild pyrethroid-resistant Anopheles arabiensis in south-eastern Tanzania Open
Background Spatial repellents that create airborne concentrations of an active ingredient (AI) within a space offer a scalable solution to further reduce transmission of malaria, by disrupting mosquito behaviours in ways that ultimately le…
View article: Poverty rate prediction using multi-modal survey and earth observation data
Poverty rate prediction using multi-modal survey and earth observation data Open
This work presents an approach for combining household demographic and living standards survey questions with features derived from satellite imagery to predict the poverty rate of a region. Our approach utilizes visual features obtained f…
View article: Rapid building damage assessment workflow: An implementation for the 2023 Rolling Fork, Mississippi tornado event
Rapid building damage assessment workflow: An implementation for the 2023 Rolling Fork, Mississippi tornado event Open
Rapid and accurate building damage assessments from high-resolution satellite imagery following a natural disaster is essential to inform and optimize first responder efforts. However, performing such building damage assessments in an auto…
View article: Automatic segmentation of prostate cancer metastases in PSMA PET/CT images using deep neural networks with weighted batch-wise dice loss
Automatic segmentation of prostate cancer metastases in PSMA PET/CT images using deep neural networks with weighted batch-wise dice loss Open
Our results demonstrate that prostate cancer metastases in PSMA PET/CT images can be detected and segmented using CNNs. The segmentation performance strongly depends on the intensity, size, and the location of lesions, and can be improved …
View article: A Biologist’s Guide to the Galaxy: Leveraging Artificial Intelligence and Very High-Resolution Satellite Imagery to Monitor Marine Mammals from Space
A Biologist’s Guide to the Galaxy: Leveraging Artificial Intelligence and Very High-Resolution Satellite Imagery to Monitor Marine Mammals from Space Open
Monitoring marine mammals is of broad interest to governments and individuals around the globe. Very high-resolution (VHR) satellites hold the promise of reaching remote and challenging locations to fill gaps in our knowledge of marine mam…
View article: Mask Conditional Synthetic Satellite Imagery
Mask Conditional Synthetic Satellite Imagery Open
In this paper we propose a mask-conditional synthetic image generation model for creating synthetic satellite imagery datasets. Given a dataset of real high-resolution images and accompanying land cover masks, we show that it is possible t…
View article: Deep learning models for COVID-19 chest x-ray classification: Preventing shortcut learning using feature disentanglement
Deep learning models for COVID-19 chest x-ray classification: Preventing shortcut learning using feature disentanglement Open
In response to the COVID-19 global pandemic, recent research has proposed creating deep learning based models that use chest radiographs (CXRs) in a variety of clinical tasks to help manage the crisis. However, the size of existing dataset…
View article: Fast building segmentation from satellite imagery and few local labels
Fast building segmentation from satellite imagery and few local labels Open
Innovations in computer vision algorithms for satellite image analysis can enable us to explore global challenges such as urbanization and land use change at the planetary level. However, domain shift problems are a common occurrence when …
View article: Effective deep learning approaches for predicting COVID-19 outcomes from chest computed tomography volumes
Effective deep learning approaches for predicting COVID-19 outcomes from chest computed tomography volumes Open
The rapid evolution of the novel coronavirus disease (COVID-19) pandemic has resulted in an urgent need for effective clinical tools to reduce transmission and manage severe illness. Numerous teams are quickly developing artificial intelli…
View article: An Artificial Intelligence Dataset for Solar Energy Locations in India
An Artificial Intelligence Dataset for Solar Energy Locations in India Open
Rapid development of renewable energy sources, particularly solar photovoltaics (PV), is critical to mitigate climate change. As a result, India has set ambitious goals to install 500 gigawatts of solar energy capacity by 2030. Given the l…
View article: An Artificial Intelligence Dataset for Solar Energy Locations in India
An Artificial Intelligence Dataset for Solar Energy Locations in India Open
To expedite development of solar energy, land use planners will need access to up-to-date and accurate geo-spatial information of PV infrastructure. In this work, we develop a machine learning model to map utility-scale solar projects acro…
View article: An Artificial Intelligence Dataset for Solar Energy Locations in India
An Artificial Intelligence Dataset for Solar Energy Locations in India Open
To expedite development of solar energy, land use planners will need access to up-to-date and accurate geo-spatial information of PV infrastructure. In this work, we develop a machine learning model to map utility-scale solar projects acro…
View article: Mapping Glacial Lakes Using Historically Guided Segmentation Models
Mapping Glacial Lakes Using Historically Guided Segmentation Models Open
In this article, we compare several approaches to segmenting glacial lakes in the Hindu Kush Himalayas in order to support glacial lake area mapping. More automatic mapping could support risk assessments of Glacial Lake Outburst Floods, a …
View article: TorchGeo: Deep Learning With Geospatial Data
TorchGeo: Deep Learning With Geospatial Data Open
Remotely sensed geospatial data are critical for applications including precision agriculture, urban planning, disaster monitoring and response, and climate change research, among others. Deep learning methods are particularly promising fo…
View article: Reducing bias and increasing utility by federated generative modeling of medical images using a centralized adversary
Reducing bias and increasing utility by federated generative modeling of medical images using a centralized adversary Open
We introduce FELICIA (FEderated LearnIng with a CentralIzed Adversary) a generative mechanism enabling collaborative learning. In particular, we show how a data owner with limited and biased data could benefit from other data owners while …
View article: Becoming Good at AI for Good
Becoming Good at AI for Good Open
AI for good (AI4G) projects involve developing and applying artificial intelligence (AI) based solutions to further goals in areas such as sustainability, health, humanitarian aid, and social justice. Developing and deploying such solution…
View article: Detecting Cattle and Elk in the Wild from Space
Detecting Cattle and Elk in the Wild from Space Open
Localizing and counting large ungulates -- hoofed mammals like cows and elk -- in very high-resolution satellite imagery is an important task for supporting ecological studies. Prior work has shown that this is feasible with deep learning …
View article: Temporal Cluster Matching for Change Detection of Structures from Satellite Imagery
Temporal Cluster Matching for Change Detection of Structures from Satellite Imagery Open
Longitudinal studies are vital to understanding dynamic changes of the planet, but labels (e.g., buildings, facilities, roads) are often available only for a single point in time. We propose a general model, Temporal Cluster Matching (TCM)…
View article: Deep learning models for COVID-19 chest x-ray classification: Preventing shortcut learning using feature disentanglement
Deep learning models for COVID-19 chest x-ray classification: Preventing shortcut learning using feature disentanglement Open
In response to the COVID-19 global pandemic, recent research has proposed creating deep learning based models that use chest radiographs (CXRs) in a variety of clinical tasks to help manage the crisis. However, the size of existing dataset…
View article: Machine Learning for Glacier Monitoring in the Hindu Kush Himalaya
Machine Learning for Glacier Monitoring in the Hindu Kush Himalaya Open
Glacier mapping is key to ecological monitoring in the hkh region. Climate change poses a risk to individuals whose livelihoods depend on the health of glacier ecosystems. In this work, we present a machine learning based approach to suppo…