10 citations · 58 across the 22 of their papers we have counts for
22 papers
HASTE: A Platform for Rapid Post-Disaster Building Damage Assessment
Caleb Robinson, Anthony Ortiz, Simone Fobi Nsutezo +8
When a large disaster strikes, responders need a map of which buildings are damaged within hours. The models that do well on public benchmarks assume matched before-and-after image…
Overhead Wildlife Locator (OWL): Benchmarking Weakly Supervised Learning for Aerial Wildlife Surveys
Isai Daniel Chacón, Zhongqi Miao, Bruno Demuro +9
Automated aerial wildlife surveys increasingly rely on deep learning, yet standard object detectors require bounding-box annotations, reported to be up to seven times slower and th…
Project SPARROW and the Future of Conservation Technology
Juan M. Lavista Ferres, Carl Chalmers, Bruno Demuro Segundo +14
Global biodiversity is declining at unprecedented rates, yet the tools available to monitor and protect ecosystems remain limited by constraints in power, connectivity, and accessi…
A strongly annotated passive acoustic dataset for tropical bird monitoring
Daniela Ruiz, Juan Sebastián Ulloa, Zhongqi Miao +11
Passive acoustic monitoring enables continuous, non-invasive biodiversity assessment across diverse ecosystems. The scale of these datasets has driven the adoption of machine learn…
The first global agricultural field boundary map at 10m resolution
Caleb Robinson, Gedeon Muhawenayo, Subash Khanal +9
The agricultural field is the natural unit at which crops are planted, managed, regulated, and reported, yet most global remote-sensing products for agriculture are only available…
WATCH: Wide-Area Archaeological Site Tracking for Change Detection
Girmaw Abebe Tadesse, Titien Bartette, Andrew Hassanali +7
Monitoring archaeological sites at scale is vital for protecting cultural heritage, yet pinpointing when disturbances occur remains difficult because visual cues are subtle and gro…
Energy Use of AI Inference, Efficiency Pathways, and Test-Time Scaling
Felipe Oviedo, Fiodar Kazhamiaka, Esha Choukse +5
As AI inference scales to billions of queries, estimates of per-query energy use are increasingly important for capacity planning, efficiency interventions, and policy. Yet many pu…
Pytorch-Wildlife: A Collaborative Deep Learning Framework for Conservation
Andres Hernandez, Zhongqi Miao, Luisa Vargas +4
The alarming decline in global biodiversity, driven by various factors, underscores the urgent need for large-scale wildlife monitoring. In response, scientists have turned to auto…
A slice classification neural network for automated classification of axial PET/CT slices from a multi-centric lymphoma dataset
Shadab Ahamed, Yixi Xu, Ingrid Bloise +5
Automated slice classification is clinically relevant since it can be incorporated into medical image segmentation workflows as a preprocessing step that would flag slices with a h…
Seeing the roads through the trees: A benchmark for modeling spatial dependencies with aerial imagery
Caleb Robinson, Isaac Corley, Anthony Ortiz +3
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…
Multimodal Foundation Models for Zero-shot Animal Species Recognition in Camera Trap Images
Zalan Fabian, Zhongqi Miao, Chunyuan Li +10
Due to deteriorating environmental conditions and increasing human activity, conservation efforts directed towards wildlife is crucial. Motion-activated camera traps constitute an…
Assessment of Differentially Private Synthetic Data for Utility and Fairness in End-to-End Machine Learning Pipelines for Tabular Data
Mayana Pereira, Meghana Kshirsagar, Sumit Mukherjee +3
Differentially private (DP) synthetic data sets are a solution for sharing data while preserving the privacy of individual data providers. Understanding the effects of utilizing DP…
Poverty rate prediction using multi-modal survey and earth observation data
Simone Fobi, Manuel Cardona, Elliott Collins +5
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…
Rapid building damage assessment workflow: An implementation for the 2023 Rolling Fork, Mississippi tornado event
Caleb Robinson, Simone Fobi Nsutezo, Anthony Ortiz +7
Rapid and accurate building damage assessments from high-resolution satellite imagery following a natural disaster is essential to inform and optimize first responder efforts. Howe…
Revisiting pre-trained remote sensing model benchmarks: resizing and normalization matters
Isaac Corley, Caleb Robinson, Rahul Dodhia +2
Research in self-supervised learning (SSL) with natural images has progressed rapidly in recent years and is now increasingly being applied to and benchmarked with datasets contain…
How effective is multifactor authentication at deterring cyberattacks?
Lucas Augusto Meyer, Sergio Romero, Gabriele Bertoli +3
This study investigates the effectiveness of multifactor authentication (MFA) in protecting commercial accounts from unauthorized access, with an additional focus on accounts with…
Fast building segmentation from satellite imagery and few local labels
Caleb Robinson, Anthony Ortiz, Hogeun Park +5
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. H…
An Artificial Intelligence Dataset for Solar Energy Locations in India
Anthony Ortiz, Dhaval Negandhi, Sagar R Mysorekar +8
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…
Mapping industrial poultry operations at scale with deep learning and aerial imagery
Caleb Robinson, Ben Chugg, Brandon Anderson +2
Concentrated Animal Feeding Operations (CAFOs) pose serious risks to air, water, and public health, but have proven to be challenging to regulate. The U.S. Government Accountabilit…
TorchGeo: Deep Learning With Geospatial Data
Adam J. Stewart, Caleb Robinson, Isaac A. Corley +3
Remotely sensed geospatial data are critical for applications including precision agriculture, urban planning, disaster monitoring and response, and climate change research, among…
MACE: A Flexible Framework for Membership Privacy Estimation in Generative Models
Yixi Xu, Sumit Mukherjee, Xiyang Liu +3
Generative machine learning models are being increasingly viewed as a way to share sensitive data between institutions. While there has been work on developing differentially priva…
Survey Data and Human Computation for Improved Flu Tracking
Stefan Wojcik, Avleen Bijral, Richard Johnston +5
While digital trace data from sources like search engines hold enormous potential for tracking and understanding human behavior, these streams of data lack information about the ac…