Kyle Bradbury | DeepAI

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Featured Co-authors

Rui Wang
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∙ 04/25/2023

Segment anything, from space?

Recently, the first foundation model developed specifically for vision t...

0 Simiao Ren, et al. ∙

∙ 10/23/2022

Transformers For Recognition In Overhead Imagery: A Reality Check

There is evidence that transformers offer state-of-the-art recognition p...

0 Francesco Luzi, et al. ∙

∙ 06/29/2021

SIMPL: Generating Synthetic Overhead Imagery to Address Zero-shot and Few-Shot Detection Problems

Recently deep neural networks (DNNs) have achieved tremendous success fo...

1 Yang Xu, et al. ∙

∙ 04/28/2021

Randomized Histogram Matching: A Simple Augmentation for Unsupervised Domain Adaptation in Overhead Imagery

Modern deep neural networks (DNNs) achieve highly accurate results for m...

0 Can Yaras, et al. ∙

∙ 01/16/2021

GridTracer: Automatic Mapping of Power Grids using Deep Learning and Overhead Imagery

Energy system information valuable for electricity access planning such ...

6 Bohao Huang, et al. ∙

∙ 01/15/2020

The Synthinel-1 dataset: a collection of high resolution synthetic overhead imagery for building segmentation

Recently deep learning - namely convolutional neural networks (CNNs) - h...

25 Fanjie Kong, et al. ∙

∙ 02/28/2019

Mapping solar array location, size, and capacity using deep learning and overhead imagery

The effective integration of distributed solar photovoltaic (PV) arrays ...

0 Jordan M. Malof, et al. ∙

∙ 05/30/2018

Dense labeling of large remote sensing imagery with convolutional neural networks: a simple and faster alternative to stitching output label maps

In this work we consider the application of convolutional neural network...

1 Bohao Huang, et al. ∙

∙ 01/11/2018

Application of a semantic segmentation convolutional neural network for accurate automatic detection and mapping of solar photovoltaic arrays in aerial imagery

We consider the problem of automatically detecting small-scale solar pho...

0 Joseph Camilo, et al. ∙

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