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Nathan Jacobs
Nathan Jacobs
Professor, Computer Science & Engineering, Washington University in St. Louis
Verified email at wustl.edu - Homepage
Title
Cited by
Cited by
Year
Wide-Area Image Geolocalization with Aerial Reference Imagery
S Workman, R Souvenir, N Jacobs
IEEE International Conference on Computer Vision (ICCV), 2015
2782015
Consistent temporal variations in many outdoor scenes
N Jacobs, N Roman, R Pless
IEEE Conference on Computer Vision and Pattern Recognition, 1-6, 2007
2202007
Predicting Ground-Level Scene Layout from Aerial Imagery
M Zhai, Z Bessinger, S Workman, N Jacobs
IEEE Conference on Computer Vision and Pattern Recognition, 2017
1852017
Geolocating static cameras
N Jacobs, S Satkin, N Roman, R Speyer, R Pless
IEEE International Conference on Computer Vision, 1-6, 2007
1432007
The global network of outdoor webcams: properties and applications
N Jacobs, W Burgin, N Fridrich, A Abrams, K Miskell, BH Braswell, ...
ACM SIGSPATIAL International Conference on Advances in Geographic …, 2009
1412009
Revisiting IM2GPS in the Deep Learning Era
N Vo, N Jacobs, J Hays
IEEE International Conference on Computer Vision, 2017
1272017
Inconsistent performance of deep learning models on mammogram classification
X Wang, G Liang, Y Zhang, H Blanton, Z Bessinger, N Jacobs
Journal of the American College of Radiology 17 (6), 796-803, 2020
1242020
Classification of whole mammogram and tomosynthesis images using deep convolutional neural networks
X Zhang, Y Zhang, E Han, N Jacobs, Q Han, X Wang, J Liu
IEEE Transactions on NanoBioscience, 2018
1202018
Detecting Vanishing Points Using Global Image Context in a Non-Manhattan World
M Zhai, S Workman, N Jacobs
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 5657-5665, 2016
1172016
On the Location Dependence of Convolutional Neural Network Features
S Workman, N & Jacobs
IEEE/ISPRS Workshop: Looking from above: When Earth observation meets vision …, 2015
1012015
Deep learning for conifer/deciduous classification of airborne LiDAR 3D point clouds representing individual trees
H Hamraz, NB Jacobs, MA Contreras, CH Clark
ISPRS Journal of Photogrammetry and Remote Sensing, 2019
952019
Horizon Lines in the Wild
S Workman, M Zhai, N Jacobs
British Machine Vision Conference, 2016
942016
DeepFocal: A Method for Direct Focal Length Estimation
S Workman, C Greenwell, M Zhai, R Baltenberger, N Jacobs
International Conference on Image Processing (ICIP), 2015
932015
Learning to Look around Objects for Top-View Representations of Outdoor Scenes
S Schulter, M Zhai, N Jacobs, M Chandraker
European Conference on Computer Vision (arXiv preprint arXiv:1803.10870), 2018
762018
Beta-amyloid and tau drive early Alzheimer's disease decline while glucose hypometabolism drives late decline
TC Hammond, X Xing, C Wang, D Ma, K Nho, PK Crane, F Elahi, ...
Communications Biology, 2020
702020
A Unified Model for Near and Remote Sensing
S Workman, M Zhai, DJ Crandall, N Jacobs
IEEE International Conference on Computer Vision, 2017
612017
Whole Mammogram Image Classification With Convolutional Neural Networks
X Zhang, Y Zhang, E Han, N Jacobs, Q Han, X Wang, J Liu
IEEE International Conference on Bioinformatics and Biomedicine, 2017
532017
Spatio-temporal deep learning approach to map deforestation in amazon rainforest
RV Maretto, LMG Fonseca, N Jacobs, TS Körting, HN Bendini, LL Parente
IEEE Geoscience and Remote Sensing Letters 18 (5), 771-775, 2020
522020
Improved Trainable Calibration Method for Neural Networks on Medical Imaging Classification
G Liang, Y Zhang, X Wang, N Jacobs
British Machine Vision Conference (BMVC), 2020
472020
Sky segmentation in the wild: An empirical study
RP Mihail, S Workman, Z Bessinger, N Jacobs
2016 IEEE Winter Conference on Applications of Computer Vision (WACV), 1-6, 2016
442016
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