no code implementations • 12 Apr 2024 • Girmaw Abebe Tadesse, Caleb Robinson, Gilles Quentin Hacheme, Akram Zaytar, Rahul Dodhia, Tsering Wangyal Shawa, Juan M. Lavista Ferres, Emmanuel H. Kreike
This study explores object detection in historical aerial photographs of Namibia to identify long-term environmental changes.
no code implementations • 11 Mar 2024 • Shadab Ahamed, Yixi Xu, Ingrid Bloise, Joo H. O, Carlos F. Uribe, Rahul Dodhia, Juan L. Ferres, Arman Rahmim
Various instances of the network were trained on 2D axial datasets created in different ways: (i) slice-level split and (ii) patient-level split; inputs of different types were used: (i) only PET slices and (ii) concatenated PET and CT slices; and different training strategies were employed: (i) center-aware (CAW) and (ii) center-agnostic (CAG).
no code implementations • 5 Mar 2024 • Akram Zaytar, Caleb Robinson, Gilles Q. Hacheme, Girmaw A. Tadesse, Rahul Dodhia, Juan M. Lavista Ferres, Lacey F. Hughey, Jared A. Stabach, Irene Amoke
Rare object detection is a fundamental task in applied geospatial machine learning, however is often challenging due to large amounts of high-resolution satellite or aerial imagery and few or no labeled positive samples to start with.
no code implementations • 13 Jan 2024 • Gilles Quentin Hacheme, Akram Zaytar, Girmaw Abebe Tadesse, Caleb Robinson, Rahul Dodhia, Juan M. Lavista Ferres, Stephen Wood
We conduct experiments to demonstrate the benefits of the improved weak labels generated by our method.
1 code implementation • 12 Jan 2024 • Caleb Robinson, Isaac Corley, Anthony Ortiz, Rahul Dodhia, Juan M. Lavista Ferres, Peyman Najafirad
In this work we propose a road segmentation benchmark dataset, Chesapeake Roads Spatial Context (RSC), for evaluating the spatial long-range context understanding of geospatial machine learning models and show how commonly used semantic segmentation models can fail at this task.
Ranked #1 on Road Segmentation on ChesapeakeRSC
1 code implementation • 16 Nov 2023 • Shadab Ahamed, Yixi Xu, Claire Gowdy, Joo H. O, Ingrid Bloise, Don Wilson, Patrick Martineau, François Bénard, Fereshteh Yousefirizi, Rahul Dodhia, Juan M. Lavista, William B. Weeks, Carlos F. Uribe, Arman Rahmim
This study performs comprehensive evaluation of four neural network architectures (UNet, SegResNet, DynUNet, and SwinUNETR) for lymphoma lesion segmentation from PET/CT images.
no code implementations • 2 Nov 2023 • Zalan Fabian, Zhongqi Miao, Chunyuan Li, Yuanhan Zhang, Ziwei Liu, Andrés Hernández, Andrés Montes-Rojas, Rafael Escucha, Laura Siabatto, Andrés Link, Pablo Arbeláez, Rahul Dodhia, Juan Lavista Ferres
In particular, we instruction tune vision-language models to generate detailed visual descriptions of camera trap images using similar terminology to experts.
no code implementations • 30 Oct 2023 • Mayana Pereira, Meghana Kshirsagar, Sumit Mukherjee, Rahul Dodhia, Juan Lavista Ferres, Rafael de Sousa
To the best of our knowledge, our work is the first that: (i) proposes a training and evaluation framework that does not assume that real data is available for testing the utility and fairness of machine learning models trained on synthetic data; (ii) presents the most extensive analysis of synthetic data set generation algorithms in terms of utility and fairness when used for training machine learning models; and (iii) encompasses several different definitions of fairness.
no code implementations • 21 Jul 2023 • Simone Fobi, Manuel Cardona, Elliott Collins, Caleb Robinson, Anthony Ortiz, Tina Sederholm, Rahul Dodhia, Juan Lavista Ferres
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.
no code implementations • 21 Jun 2023 • Caleb Robinson, Simone Fobi Nsutezo, Anthony Ortiz, Tina Sederholm, Rahul Dodhia, Cameron Birge, Kasie Richards, Kris Pitcher, Paulo Duarte, Juan M. Lavista Ferres
Rapid and accurate building damage assessments from high-resolution satellite imagery following a natural disaster is essential to inform and optimize first responder efforts.
1 code implementation • 22 May 2023 • Isaac Corley, Caleb Robinson, Rahul Dodhia, Juan M. Lavista Ferres, Peyman Najafirad
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 containing remotely sensed imagery.
no code implementations • 16 Nov 2022 • Md Nasir, Tina Sederholm, Anshu Sharma, Sundeep Reddy Mallu, Sumedh Ranjan Ghatage, Rahul Dodhia, Juan Lavista Ferres
Then a risk score assessment model was employed, using the determined dwelling type along with an inundation model of the regions.
1 code implementation • 10 Jun 2022 • Caleb Robinson, Anthony Ortiz, Hogeun Park, Nancy Lozano Gracia, Jon Kher Kaw, Tina Sederholm, Rahul Dodhia, Juan M. Lavista Ferres
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.
no code implementations • 28 Jul 2021 • Anusua Trivedi, Jocelyn Desbiens, Ron Gross, Sunil Gupta, Rahul Dodhia, Juan Lavista Ferres
Conclusion: In the case of DR, most of the disease biomarkers are related topologically to the vasculature.
no code implementations • 15 Jun 2021 • Mayana Pereira, Meghana Kshirsagar, Sumit Mukherjee, Rahul Dodhia, Juan Lavista Ferres
Diferentially private (DP) synthetic datasets are a powerful approach for training machine learning models while respecting the privacy of individual data providers.
no code implementations • 3 Jun 2021 • Anusua Trivedi, Alyssa Suhm, Prathamesh Mahankal, Subhiksha Mukuntharaj, Meghana D. Parab, Malvika Mohan, Meredith Berger, Arathi Sethumadhavan, Ashish Jaiman, Rahul Dodhia
The rise in online misinformation in recent years threatens democracies by distorting authentic public discourse and causing confusion, fear, and even, in extreme cases, violence.
no code implementations • 4 May 2021 • Anusua Trivedi, Mohit Jain, Nikhil Kumar Gupta, Markus Hinsche, Prashant Singh, Markus Matiaschek, Tristan Behrens, Mirco Militeri, Cameron Birge, Shivangi Kaushik, Archisman Mohapatra, Rita Chatterjee, Rahul Dodhia, Juan Lavista Ferres
Malnutrition is a global health crisis and is the leading cause of death among children under five.
no code implementations • 5 Oct 2020 • Mayana Pereira, Rahul Dodhia, Hyrum Anderson, Richard Brown
With such restrictions in place, the development of CSAM machine learning detection systems based on file metadata uncovers several opportunities.
no code implementations • 4 Oct 2020 • Anusua Trivedi, Sreya Muppalla, Shreyaan Pathak, Azadeh Mobasher, Pawel Janowski, Rahul Dodhia, Juan M. Lavista Ferres
Bissoto et al. experimented with different bounding-box based masks and showed that deep learning models could classify skin lesion images without clinically meaningful information in the input data.
no code implementations • 11 Sep 2020 • Yixi Xu, Sumit Mukherjee, Xiyang Liu, Shruti Tople, Rahul Dodhia, Juan Lavista Ferres
In this work, we propose the first formal framework for membership privacy estimation in generative models.