Get our free extension to see links to code for papers anywhere online!

Chrome logo Add to Chrome

Firefox logo Add to Firefox
Picture for Andrew Feng

Andrew Feng

Utilizing Satellite Imagery Datasets and Machine Learning Data Models to Evaluate Infrastructure Change in Undeveloped Regions


Sep 01, 2020
Kyle McCullough, Andrew Feng, Meida Chen, Ryan McAlinden

Figure 1 for Utilizing Satellite Imagery Datasets and Machine Learning Data Models to Evaluate Infrastructure Change in Undeveloped Regions
Figure 2 for Utilizing Satellite Imagery Datasets and Machine Learning Data Models to Evaluate Infrastructure Change in Undeveloped Regions
Figure 3 for Utilizing Satellite Imagery Datasets and Machine Learning Data Models to Evaluate Infrastructure Change in Undeveloped Regions
Figure 4 for Utilizing Satellite Imagery Datasets and Machine Learning Data Models to Evaluate Infrastructure Change in Undeveloped Regions
* Interservice/Industry Training, Simulation, and Education Conference (I/ITSEC) 2020 
  Access Paper or Ask Questions

Semantic Segmentation and Data Fusion of Microsoft Bing 3D Cities and Small UAV-based Photogrammetric Data


Aug 21, 2020
Meida Chen, Andrew Feng, Kyle McCullough, Pratusha Bhuvana Prasad, Ryan McAlinden, Lucio Soibelman

Figure 1 for Semantic Segmentation and Data Fusion of Microsoft Bing 3D Cities and Small UAV-based Photogrammetric Data
Figure 2 for Semantic Segmentation and Data Fusion of Microsoft Bing 3D Cities and Small UAV-based Photogrammetric Data
Figure 3 for Semantic Segmentation and Data Fusion of Microsoft Bing 3D Cities and Small UAV-based Photogrammetric Data
Figure 4 for Semantic Segmentation and Data Fusion of Microsoft Bing 3D Cities and Small UAV-based Photogrammetric Data
* Interservice/Industry Training, Simulation, and Education Conference (I/ITSEC) 2020 
  Access Paper or Ask Questions

Generating synthetic photogrammetric data for training deep learning based 3D point cloud segmentation models


Aug 21, 2020
Meida Chen, Andrew Feng, Kyle McCullough, Pratusha Bhuvana Prasad, Ryan McAlinden, Lucio Soibelman

Figure 1 for Generating synthetic photogrammetric data for training deep learning based 3D point cloud segmentation models
Figure 2 for Generating synthetic photogrammetric data for training deep learning based 3D point cloud segmentation models
Figure 3 for Generating synthetic photogrammetric data for training deep learning based 3D point cloud segmentation models
Figure 4 for Generating synthetic photogrammetric data for training deep learning based 3D point cloud segmentation models
* Interservice/Industry Training, Simulation, and Education Conference (I/ITSEC) 2020 
  Access Paper or Ask Questions

Fully Automated Photogrammetric Data Segmentation and Object Information Extraction Approach for Creating Simulation Terrain


Aug 09, 2020
Meida Chen, Andrew Feng, Kyle McCullough, Pratusha Bhuvana Prasad, Ryan McAlinden, Lucio Soibelman, Mike Enloe

* Interservice/Industry Training, Simulation, and Education Conference (I/ITSEC) 2019 
  Access Paper or Ask Questions

Privacy-preserving Federated Brain Tumour Segmentation


Oct 02, 2019
Wenqi Li, Fausto Milletarì, Daguang Xu, Nicola Rieke, Jonny Hancox, Wentao Zhu, Maximilian Baust, Yan Cheng, Sébastien Ourselin, M. Jorge Cardoso, Andrew Feng

Figure 1 for Privacy-preserving Federated Brain Tumour Segmentation
Figure 2 for Privacy-preserving Federated Brain Tumour Segmentation
Figure 3 for Privacy-preserving Federated Brain Tumour Segmentation
* MICCAI MLMI 2019 
  Access Paper or Ask Questions

Scalable Semantic Matching of Queries to Ads in Sponsored Search Advertising


Jul 07, 2016
Mihajlo Grbovic, Nemanja Djuric, Vladan Radosavljevic, Fabrizio Silvestri, Ricardo Baeza-Yates, Andrew Feng, Erik Ordentlich, Lee Yang, Gavin Owens

Figure 1 for Scalable Semantic Matching of Queries to Ads in Sponsored Search Advertising
Figure 2 for Scalable Semantic Matching of Queries to Ads in Sponsored Search Advertising
Figure 3 for Scalable Semantic Matching of Queries to Ads in Sponsored Search Advertising
Figure 4 for Scalable Semantic Matching of Queries to Ads in Sponsored Search Advertising
* 39th International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2016, Pisa, Italy 
 * 10 pages, 4 figures, 39th International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2016, Pisa, Italy 
  Access Paper or Ask Questions