Caleb Robinson

According to our database, Caleb Robinson authored at least 45 papers between 2016 and 2024.

Collaborative distances:

• Dijkstra number of three.
• Erdős number of four.

2024

Fields of The World: A Machine Learning Benchmark Dataset For Global Agricultural Field Boundary Segmentation.

Hannah Kerner, Snehal Chaudhari, Aninda Ghosh, Caleb Robinson, Adeel Ahmad, Eddie Choi, Nathan Jacobs, Chris Holmes, Matthias Mohr, Rahul Dodhia, Juan M. Lavista Ferres, Jennifer Marcus

CoRR, 2024

Analyzing Decades-Long Environmental Changes in Namibia Using Archival Aerial Photography and Deep Learning.

Girmaw Abebe Tadesse, Caleb Robinson, Gilles Quentin Hacheme, Akram Zaytar, Rahul Dodhia, Tsering Wangyal Shawa, Juan M. Lavista Ferres, Emmanuel H. Kreike

CoRR, 2024

Bootstrapping Rare Object Detection in High-Resolution Satellite Imagery.

Akram Zaytar, Caleb Robinson, Gilles Quentin Hacheme, Girmaw Abebe Tadesse, Rahul Dodhia, Juan M. Lavista Ferres, Lacey F. Hughey, Jared A. Stabach, Irene Amoke

CoRR, 2024

A Change Detection Reality Check.

Isaac Corley, Caleb Robinson, Anthony Ortiz

CoRR, 2024

Mission Critical - Satellite Data is a Distinct Modality in Machine Learning.

Esther Rolf, Konstantin Klemmer, Caleb Robinson, Hannah Kerner

CoRR, 2024

Seeing the roads through the trees: A benchmark for modeling spatial dependencies with aerial imagery.

Caleb Robinson, Isaac Corley, Anthony Ortiz, Rahul Dodhia, Juan M. Lavista Ferres, Peyman Najafirad

CoRR, 2024

Weak Labeling for Cropland Mapping in Africa.

Gilles Quentin Hacheme, Akram Zaytar, Girmaw Abebe Tadesse, Caleb Robinson, Rahul Dodhia, Juan M. Lavista Ferres, Stephen Wood

Proceedings of the IGARSS 2024, 2024

Position: Mission Critical - Satellite Data is a Distinct Modality in Machine Learning.

Esther Rolf, Konstantin Klemmer, Caleb Robinson, Hannah Kerner

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Revisiting pre-trained remote sensing model benchmarks: resizing and normalization matters.

Isaac Corley, Caleb Robinson, Rahul Dodhia, Juan M. Lavista Ferres, Peyman Najafirad

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024

2023

Harnessing AI and robotics in humanitarian assistance and disaster response.

Thomas Manzini, Robin R. Murphy, Eric T. Heim, Caleb Robinson, Guido Zarrella, Ritwik Gupta

Sci. Robotics, July, 2023

Open Datasheets: Machine-readable Documentation for Open Datasets and Responsible AI Assessments.

Anthony Cintron Roman, Jennifer Wortman Vaughan, Valerie See, Steph Ballard, Nicolas Schifano, Jehu Torres Vega, Caleb Robinson, Juan M. Lavista Ferres

CoRR, 2023

SatCLIP: Global, General-Purpose Location Embeddings with Satellite Imagery.

Konstantin Klemmer, Esther Rolf, Caleb Robinson, Lester Mackey, Marc Rußwurm

CoRR, 2023

Open Data on GitHub: Unlocking the Potential of AI.

Anthony Cintron Roman, Kevin Xu, Arfon Smith, Jehu Torres Vega, Caleb Robinson, Juan M. Lavista Ferres

CoRR, 2023

Mask Conditional Synthetic Satellite Imagery.

Van Anh Le, Varshini Reddy, Zixi Chen, Mengyuan Li, Xinran Tang, Anthony Ortiz, Simone Fobi Nsutezo, Caleb Robinson

CoRR, 2023

SSL4EO-L: Datasets and Foundation Models for Landsat Imagery.

Adam J. Stewart, Nils Lehmann, Isaac A. Corley, Yi Wang, Yi-Chia Chang, Nassim Ait Ali Braham, Shradha Sehgal, Caleb Robinson, Arindam Banerjee

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Rapid building damage assessment workflow: An implementation for the 2023 Rolling Fork, Mississippi tornado event.

Caleb Robinson, Simone Fobi Nsutezo, Anthony Ortiz, Tina Sederholm, Rahul Dodhia, Cameron Birge, Kasie Richards, Kris Pitcher, Paulo Duarte, Juan M. Lavista Ferres

Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

Poverty rate prediction using multi-modal survey and earth observation data.

Simone Fobi, Manuel Cardona, Elliott Collins, Caleb Robinson, Anthony Ortiz, Tina Sederholm, Rahul Dodhia, Juan Lavista Ferres

Proceedings of the 6th ACM SIGCAS/SIGCHI Conference on Computing and Sustainable Societies, 2023

2022

Mapping Industrial Poultry Operations at Scale With Deep Learning and Aerial Imagery.

Caleb Robinson, Ben Chugg, Brandon R. Anderson, Juan M. Lavista Ferres, Daniel E. Ho

IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2022

The Outcome of the 2021 IEEE GRSS Data Fusion Contest - Track MSD: Multitemporal Semantic Change Detection.

Zhuohong Li, Fangxiao Lu, Hongyan Zhang, Lilin Tu, Jiayi Li, Xin Huang, Caleb Robinson, Nikolay Malkin, Nebojsa Jojic, Pedram Ghamisi, Ronny Hänsch, Naoto Yokoya

IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2022

An Artificial Intelligence Dataset for Solar Energy Locations in India.

Anthony Ortiz, Dhaval Negandhi, Sagar R. Mysorekar, Joseph Kiesecker, Shivaprakash K. Nagaraju, Caleb Robinson, Priyal Bhatia, Aditi Khurana, Jane Wang, Felipe Oviedo, Juan Lavista Ferres

CoRR, 2022

Resolving label uncertainty with implicit posterior models.

Esther Rolf, Nikolay Malkin, Alexandros Graikos, Ana Jojic, Caleb Robinson, Nebojsa Jojic

Proceedings of the Uncertainty in Artificial Intelligence, 2022

On the Deployment of Post-Disaster Building Damage Assessment Tools using Satellite Imagery: A Deep Learning Approach.

Shahrzad Gholami, Caleb Robinson, Anthony Ortiz, Siyu Yang, Jacopo Margutti, Cameron Birge, Rahul Dodhia, Juan Lavista Ferres

Proceedings of the IEEE International Conference on Data Mining Workshops, 2022

TorchGeo: deep learning with geospatial data.

Adam J. Stewart, Caleb Robinson, Isaac A. Corley, Anthony Ortiz, Juan M. Lavista Ferres, Arindam Banerjee

Proceedings of the 30th International Conference on Advances in Geographic Information Systems, 2022

Fast building segmentation from satellite imagery and few local labels.

Caleb Robinson, Anthony Ortiz, Hogeun Park, Nancy Lozano-Gracia, Jon Kher Kaw, Tina Sederholm, Rahul Dodhia, Juan M. Lavista Ferres

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2022

2021

Global Land-Cover Mapping With Weak Supervision: Outcome of the 2020 IEEE GRSS Data Fusion Contest.

Caleb Robinson, Kolya Malkin, Nebojsa Jojic, Huijun Chen, Rongjun Qin, Changlin Xiao, Michael Schmitt, Pedram Ghamisi, Ronny Hänsch, Naoto Yokoya

IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2021

Detecting Cattle and Elk in the Wild from Space.

Caleb Robinson, Anthony Ortiz, Lacey Hughey, Jared A. Stabach, Juan M. Lavista Ferres

CoRR, 2021

High-resolution land cover change from low-resolution labels: Simple baselines for the 2021 IEEE GRSS Data Fusion Contest.

Nikolay Malkin, Caleb Robinson, Nebojsa Jojic

CoRR, 2021

From Local Algorithms to Global Results: Human-Machine Collaboration for Robust Analysis of Geographically Diverse Imagery.

Nebojsa Jojic, Nikolay Malkin, Caleb Robinson, Anthony Ortiz

Proceedings of the IEEE International Geoscience and Remote Sensing Symposium, 2021

Reducing bias and increasing utility by federated generative modeling of medical images using a centralized adversary.

Jean-François Rajotte, Sumit Mukherjee, Caleb Robinson, Anthony Ortiz, Christopher West, Juan M. Lavista Ferres, Raymond T. Ng

Proceedings of the GoodIT '21: Conference on Information Technology for Social Good, 2021

Temporal Cluster Matching for Change Detection of Structures from Satellite Imagery.

Caleb Robinson, Anthony Ortiz, Juan M. Lavista Ferres, Brandon R. Anderson, Daniel E. Ho

Proceedings of the COMPASS '21: ACM SIGCAS Conference on Computing and Sustainable Societies, Virtual Event, Australia, 28 June 2021, 2021

Becoming Good at AI for Good.

Meghana Kshirsagar, Caleb Robinson, Siyu Yang, Shahrzad Gholami, Ivan S. Klyuzhin, Sumit Mukherjee, Md Nasir, Anthony Ortiz, Felipe Oviedo, Darren Tanner, Anusua Trivedi, Yixi Xu, Ming Zhong, Bistra Dilkina, Rahul Dodhia, Juan M. Lavista Ferres

Proceedings of the AIES '21: AAAI/ACM Conference on AI, 2021

2020

Summit: Scaling Deep Learning Interpretability by Visualizing Activation and Attribution Summarizations.

Fred Hohman, Haekyu Park, Caleb Robinson, Duen Horng (Polo) Chau

IEEE Trans. Vis. Comput. Graph., 2020

Model Generalization in Deep Learning Applications for Land Cover Mapping.

Lucas Hu, Caleb Robinson, Bistra Dilkina

CoRR, 2020

Mining self-similarity: Label super-resolution with epitomic representations.

Kolya Malkin, Anthony Ortiz, Caleb Robinson, Nebojsa Jojic

CoRR, 2020

Weakly Supervised Semantic Segmentation in the 2020 IEEE GRSS Data Fusion Contest.

Caleb Robinson, Kolya Malkin, Lucas Hu, Bistra Dilkina, Nebojsa Jojic

Proceedings of the IEEE International Geoscience and Remote Sensing Symposium, 2020

Local Context Normalization: Revisiting Local Normalization.

Anthony Ortiz, Caleb Robinson, Dan Morris, Olac Fuentes, Christopher Kiekintveld, Md Mahmudulla Hassan, Nebojsa Jojic

Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020

Human-Machine Collaboration for Fast Land Cover Mapping.

Caleb Robinson, Anthony Ortiz, Kolya Malkin, Blake Elias, Andi Peng, Dan Morris, Bistra Dilkina, Nebojsa Jojic

Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019

Migration patterns under different scenarios of sea level rise.

Caleb Robinson, Bistra Dilkina, Juan Moreno-Cruz

CoRR, 2019

Label super-resolution networks.

Kolya Malkin, Caleb Robinson, Le Hou, Rachel Soobitsky, Jacob Czawlytko, Dimitris Samaras, Joel H. Saltz, Lucas Joppa, Nebojsa Jojic

Proceedings of the 7th International Conference on Learning Representations, 2019

Large Scale High-Resolution Land Cover Mapping With Multi-Resolution Data.

Caleb Robinson, Le Hou, Kolya Malkin, Rachel Soobitsky, Jacob Czawlytko, Bistra Dilkina, Nebojsa Jojic

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2019

2018

Toward a common object model for integrated transportation and land use models.

Caleb Robinson, John Crittenden, Zhongming Lu, Richard Fujimoto

Proceedings of the Annual Simulation Symposium, 2018

A Machine Learning Approach to Modeling Human Migration.

Caleb Robinson, Bistra Dilkina

Proceedings of the 1st ACM SIGCAS Conference on Computing and Sustainable Societies, 2018

Infrastructure Resilience for Climate Adaptation.

Amrita Gupta, Caleb Robinson, Bistra Dilkina

Proceedings of the 1st ACM SIGCAS Conference on Computing and Sustainable Societies, 2018

2017

A Deep Learning Approach for Population Estimation from Satellite Imagery.

Caleb Robinson, Fred Hohman, Bistra Dilkina

Proceedings of the 1st ACM SIGSPATIAL Workshop on Geospatial Humanities, 2017

2016

Network optimization of food flows in the U.S.

Caleb Robinson, Arezoo Shirazi, Mengmeng Liu, Bistra Dilkina

Proceedings of the 2016 IEEE International Conference on Big Data (IEEE BigData 2016), 2016