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ORCIDGreg Olmschenk
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2020 – today
- 2024
[i4]Greg Olmschenk, Richard K. Barry, Stela Ishitani Silva, Brian P. Powell, Ethan Kruse, Jeremy D. Schnittman, Agnieszka M. Cieplak, Thomas Barclay, Siddhant Solanki, Bianca Ortega, John Baker, Yesenia Helem Salinas Mamani:
Short-Period Variables in TESS Full-Frame Image Light Curves Identified via Convolutional Neural Networks. CoRR abs/2402.12369 (2024)- 2021
- [j2]Greg Olmschenk, Xuan Wang, Hao Tang
, Zhigang Zhu:
Impact of Labeling Schemes on Dense Crowd Counting Using Convolutional Neural Networks with Multiscale Upsampling. Int. J. Pattern Recognit. Artif. Intell. 35(16): 2160012:1-2160012:31 (2021) - [i3]Greg Olmschenk, Stela Ishitani Silva, Gioia Rau, Richard K. Barry, Ethan Kruse, Luca Cacciapuoti, Veselin Kostov, Brian P. Powell, Edward Wyrwas, Jeremy D. Schnittman, Thomas Barclay:
Identifying Planetary Transit Candidates in TESS Full-Frame Image Light Curves via Convolutional Neural Networks. CoRR abs/2101.10919 (2021) - 2020
- [c9]Greg Olmschenk, Hao Tang, Zhigang Zhu:
Improving Dense Crowd Counting Convolutional Neural Networks using Inverse k-Nearest Neighbor Maps and Multiscale Upsampling. VISIGRAPP (5: VISAPP) 2020: 185-195
2010 – 2019
- 2019
- [b1]Greg Olmschenk:
Semi-supervised Regression with Generative Adversarial Networks Using Minimal Labeled Data. City University of New York, USA, 2019 - [j1]Greg Olmschenk, Zhigang Zhu, Hao Tang:
Generalizing semi-supervised generative adversarial networks to regression using feature contrasting. Comput. Vis. Image Underst. 186: 1-12 (2019) - [c8]Greg Olmschenk, Jin Chen, Hao Tang, Zhigang Zhu:
Dense Crowd Counting Convolutional Neural Networks with Minimal Data using Semi-Supervised Dual-Goal Generative Adversarial Networks. CVPR Workshops 2019 - [i2]Greg Olmschenk, Hao Tang, Zhigang Zhu:
Improving Dense Crowd Counting Convolutional Neural Networks using Inverse k-Nearest Neighbor Maps and Multiscale Upsampling. CoRR abs/1902.05379 (2019) - 2018
- [c7]Vishnu Nair, Manjekar Budhai, Greg Olmschenk, William H. Seiple, Zhigang Zhu:
ASSIST: Personalized Indoor Navigation via Multimodal Sensors and High-Level Semantic Information. ECCV Workshops (6) 2018: 128-143 - [c6]Greg Olmschenk, Hao Tang, Zhigang Zhu:
Crowd Counting with Minimal Data Using Generative Adversarial Networks for Multiple Target Regression. WACV 2018: 1151-1159 - [i1]Greg Olmschenk, Zhigang Zhu, Hao Tang:
Generalizing semi-supervised generative adversarial networks to regression. CoRR abs/1811.11269 (2018) - 2017
- [c5]Greg Olmschenk, Hao Tang, Zhigang Zhu:
Pitch and Roll Camera Orientation from a Single 2D Image Using Convolutional Neural Networks. CRV 2017: 261-268 - 2015
- [c4]Wai L. Khoo, Greg Olmschenk, Zhigang Zhu, Tony Ro:
Evaluating Crowd Sourced Navigation for the Visually Impaired in a Virtual Environment. IEEE MS 2015: 431-437 - [c3]Greg Olmschenk, Zhigang Zhu:
Mobile real-time single image 3D corridor reconstruction using J-Linkage. MVA 2015: 94-97 - [c2]Greg Olmschenk, Christopher Yang, Zhigang Zhu, Hanghang Tong, William H. Seiple:
Mobile Crowd Assisted Navigation for the Visually Impaired. UIC/ATC/ScalCom 2015: 324-327 - 2014
- [c1]Greg Olmschenk, Zhigang Zhu:
3D Hallway Modeling Using a Single Image. CVPR Workshops 2014: 158-164
Coauthor Index
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