Jordan M. Malof | DeepAI

AI Chat

Featured Co-authors

Rui Wang
176 publications
Yang Xu
89 publications
Yang Deng
39 publications
Daniël Reichman
17 publications
Leslie M. Collins
15 publications
Kyle Bradbury
9 publications
Boning Li
8 publications
Simiao Ren
7 publications
Bohao Huang
6 publications
Fanjie Kong
5 publications
Willie J. Padilla
4 publications

∙ 04/25/2023

Segment anything, from space?

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

0 Simiao Ren, et al. ∙

∙ 12/24/2022

Meta-Learning for Color-to-Infrared Cross-Modal Style Transfer

Recent object detection models for infrared (IR) imagery are based upon ...

0 Evelyn A. Stump, et al. ∙

∙ 11/25/2022

Mixture Manifold Networks: A Computationally Efficient Baseline for Inverse Modeling

We propose and show the efficacy of a new method to address generic inve...

0 Gregory P. Spell, et al. ∙

∙ 09/19/2022

Meta-simulation for the Automated Design of Synthetic Overhead Imagery

The use of synthetic (or simulated) data for training machine learning m...

0 Handi Yu, et al. ∙

∙ 12/19/2021

Inverse deep learning methods and benchmarks for artificial electromagnetic material design

Deep learning (DL) inverse techniques have increased the speed of artifi...

0 Simiao Ren, 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. ∙

∙ 01/15/2020

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. ∙

∙ 06/04/2018

gprHOG: Several Simple Improvements to the Histogram of Oriented Gradients Feature for Threat Detection in Ground-Penetrating Radar

The ground penetrating radar (GPR) is one of the most successful remote ...

0 Daniël Reichman, 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. ∙

∙ 03/10/2018

A Large-Scale Multi-Institutional Evaluation of Advanced Discrimination Algorithms for Buried Threat Detection in Ground Penetrating Radar

In this paper we consider the development of algorithms for the automati...

0 Jordan M. Malof, 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. ∙

∙ 02/09/2017

A large comparison of feature-based approaches for buried target classification in forward-looking ground-penetrating radar

Forward-looking ground-penetrating radar (FLGPR) has recently been inves...

0 Joseph A. Camilo, et al. ∙

∙ 12/11/2016

On Choosing Training and Testing Data for Supervised Algorithms in Ground Penetrating Radar Data for Buried Threat Detection

Ground penetrating radar (GPR) is one of the most popular and successful...

0 Daniël Reichman, et al. ∙

Are you a researcher?
Expose your work
to one of the largest
A.I. communities in the world