1 code implementation • 10 Feb 2024 • Isaac Corley, Caleb Robinson, Anthony Ortiz
In recent years, there has been an explosion of proposed change detection deep learning architectures in the remote sensing literature.
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
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 • 8 Feb 2023 • Van Anh Le, Varshini Reddy, Zixi Chen, Mengyuan Li, Xinran Tang, Anthony Ortiz, Simone Fobi Nsutezo, Caleb Robinson
In this paper we propose a mask-conditional synthetic image generation model for creating synthetic satellite imagery datasets.
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.
1 code implementation • 31 Jan 2022 • 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
Using this dataset, we measure the solar footprint across India and quantified the degree of landcover modification associated with the development of PV infrastructure.
1 code implementation • 17 Nov 2021 • Adam J. Stewart, Caleb Robinson, Isaac A. Corley, Anthony Ortiz, Juan M. Lavista Ferres, Arindam Banerjee
Deep learning methods are particularly promising for modeling many remote sensing tasks given the success of deep neural networks in similar computer vision tasks and the sheer volume of remotely sensed imagery available.
no code implementations • 29 Jun 2021 • Caleb Robinson, Anthony Ortiz, Lacey Hughey, Jared A. Stabach, Juan M. Lavista Ferres
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.
1 code implementation • 17 Mar 2021 • Caleb Robinson, Anthony Ortiz, Juan M. Lavista Ferres, Brandon Anderson, Daniel E. Ho
For instance, in rural settings, the pre-construction area may look similar to the surrounding environment until the building is constructed.
no code implementations • 18 Jan 2021 • Jean-Francois Rajotte, Sumit Mukherjee, Caleb Robinson, Anthony Ortiz, Christopher West, Juan Lavista Ferres, Raymond T Ng
We show that by using the FELICIA mechanism, a data owner with limited image samples can generate high-quality synthetic images with high utility while neither data owners has to provide access to its data.
no code implementations • 1 Jan 2021 • Anthony Ortiz, Kris Sankaran, Olac Fuentes, Christopher Kiekintveld, Pascal Vincent, Yoshua Bengio, Doina Precup
In this work we tackle the problem of out-of-distribution generalization through conditional computation.
1 code implementation • 9 Dec 2020 • Shimaa Baraka, Benjamin Akera, Bibek Aryal, Tenzing Sherpa, Finu Shresta, Anthony Ortiz, Kris Sankaran, Juan Lavista Ferres, Mir Matin, Yoshua Bengio
Glacier mapping is key to ecological monitoring in the hkh region.
1 code implementation • ECCV 2020 • Nikolay Malkin, Anthony Ortiz, Caleb Robinson, Nebojsa Jojic
We show that simple patch-based models, such as epitomes, can have superior performance to the current state of the art in semantic segmentation and label super-resolution, which uses deep convolutional neural networks.
1 code implementation • CVPR 2020 • Anthony Ortiz, Caleb Robinson, Dan Morris, Olac Fuentes, Christopher Kiekintveld, Md Mahmudulla Hassan, Nebojsa Jojic
In many vision applications the local spatial context of the features is important, but most common normalization schemes including Group Normalization (GN), Instance Normalization (IN), and Layer Normalization (LN) normalize over the entire spatial dimension of a feature.
no code implementations • 31 Jul 2019 • Vincent Michalski, Vikram Voleti, Samira Ebrahimi Kahou, Anthony Ortiz, Pascal Vincent, Chris Pal, Doina Precup
Batch normalization has been widely used to improve optimization in deep neural networks.
no code implementations • 10 Jun 2019 • Caleb Robinson, Anthony Ortiz, Kolya Malkin, Blake Elias, Andi Peng, Dan Morris, Bistra Dilkina, Nebojsa Jojic
This bi-directional feedback loop allows humans to learn how the model responds to new data.
no code implementations • 27 Oct 2018 • Dalton Rosario, Anthony Ortiz, Olac Fuentes
We focus on the automatic 3D terrain segmentation problem using hyperspectral shortwave IR (HS-SWIR) imagery and 3D Digital Elevation Models (DEM).
no code implementations • 29 Nov 2017 • Dalton Rosario, Christoph Borel, Damon Conover, Ryan McAlinden, Anthony Ortiz, Sarah Shiver, Blair Simon
Following an initiative formalized in April 2016 formally known as ARL West between the U. S. Army Research Laboratory (ARL) and University of Southern California's Institute for Creative Technologies (USC ICT), a field experiment was coordinated and executed in the summer of 2016 by ARL, USC ICT, and Headwall Photonics.