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Found 13 papers, 6 papers with code
An Artificial Intelligence Dataset for Solar Energy Locations in India
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
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.
Detecting Cattle and Elk in the Wild from Space
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
For instance, in rural settings, the pre-construction area may look similar to the surrounding environment until the building is constructed.
Reducing bias and increasing utility by federated generative modeling of medical images using a centralized adversary
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.
Conditional Networks
In this work we tackle the problem of out-of-distribution generalization through conditional computation.
Machine Learning for Glacier Monitoring in the Hindu Kush Himalaya
Glacier mapping is key to ecological monitoring in the hkh region.
Mining self-similarity: Label super-resolution with epitomic representations
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.
Local Context Normalization: Revisiting Local Normalization
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.
An Empirical Study of Batch Normalization and Group Normalization in Conditional Computation
Batch normalization has been widely used to improve optimization in deep neural networks.
Human-Machine Collaboration for Fast Land Cover Mapping
This bi-directional feedback loop allows humans to learn how the model responds to new data.
3D Terrain Segmentation in the SWIR Spectrum
We focus on the automatic 3D terrain segmentation problem using hyperspectral shortwave IR (HS-SWIR) imagery and 3D Digital Elevation Models (DEM).
Small Drone Field Experiment: Data Collection & Processing
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.
