Search Results for author: Anthony Ortiz

Found 13 papers, 6 papers with code

An Artificial Intelligence Dataset for Solar Energy Locations in India

1 code implementation31 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

Given the large footprint projected to meet these renewable energy targets the potential for land use conflicts over environmental and social values is high.

TorchGeo: deep learning with geospatial data

1 code implementation17 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.

Transfer Learning

Detecting Cattle and Elk in the Wild from Space

no code implementations29 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.

Temporal Cluster Matching for Change Detection of Structures from Satellite Imagery

1 code implementation17 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.

Change Detection Data Augmentation +1

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

no code implementations18 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.

Federated Learning Lesion Classification +1

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

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.

Semantic Segmentation Super-Resolution

Local Context Normalization: Revisiting Local Normalization

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.

Instance Segmentation Object Detection +2

3D Terrain Segmentation in the SWIR Spectrum

no code implementations27 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).

Image-Based Localization

Small Drone Field Experiment: Data Collection & Processing

no code implementations29 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.

3D Reconstruction Scene Understanding

Cannot find the paper you are looking for? You can Submit a new open access paper.