Search Results for author: Caleb Robinson

Found 17 papers, 10 papers with code

Resolving label uncertainty with implicit posterior models

1 code implementation28 Feb 2022 Esther Rolf, Nikolay Malkin, Alexandros Graikos, Ana Jojic, Caleb Robinson, Nebojsa Jojic

We propose a method for jointly inferring labels across a collection of data samples, where each sample consists of an observation and a prior belief about the label.

Common Sense Reasoning Text Classification

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

Resolving label uncertainty with implicit generative models

no code implementations29 Sep 2021 Esther Rolf, Nikolay Malkin, Alexandros Graikos, Ana Jojic, Caleb Robinson, Nebojsa Jojic

In prediction problems, coarse and imprecise sources of input can provide rich information about labels, but are not readily used by discriminative learners.

Common Sense Reasoning Text Classification

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

Model Generalization in Deep Learning Applications for Land Cover Mapping

2 code implementations9 Aug 2020 Lucas Hu, Caleb Robinson, Bistra Dilkina

Recent work has shown that deep learning models can be used to classify land-use data from geospatial satellite imagery.

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

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

1 code implementation CVPR 2019 Caleb Robinson, Le Hou, Kolya Malkin, Rachel Soobitsky, Jacob Czawlytko, Bistra Dilkina, Nebojsa Jojic

The land cover mapping problem, at country-level scales, is challenging for common deep learning methods due to the scarcity of high-resolution labels, as well as variation in geography and quality of input images.

Label super-resolution networks

no code implementations ICLR 2019 Kolya Malkin, Caleb Robinson, Le Hou, Nebojsa Jojic

We present a deep learning-based method for super-resolving coarse (low-resolution) labels assigned to groups of image pixels into pixel-level (high-resolution) labels, given the joint distribution between those low- and high-resolution labels.

Semantic Segmentation Super-Resolution

A Machine Learning Approach to Modeling Human Migration

no code implementations15 Nov 2017 Caleb Robinson, Bistra Dilkina

Traditional human mobility models, such as gravity models or the more recent radiation model, predict human mobility flows based on population and distance features only.

A Deep Learning Approach for Population Estimation from Satellite Imagery

no code implementations30 Aug 2017 Caleb Robinson, Fred Hohman, Bistra Dilkina

We validate these models in two ways: quantitatively, by comparing our model's grid cell estimates aggregated at a county-level to several US Census county-level population projections, and qualitatively, by directly interpreting the model's predictions in terms of the satellite image inputs.

Decision Making

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