Greg Olmschenk

Olmschenk, G. ., Wang, X. ., Tang, H. ., & Zhu, Z. . (2021). Impact of Labeling Schemes on Dense Crowd Counting Using Convolutional Neural Networks with Multiscale Upsampling. International Journal of Pattern Recognition and Artificial Intelligence, 35(16). http://doi.org/10.1142/S0218001421600120

Nair, V. ., Olmschenk, G. ., Seiple, W. H., & Zhu, Z. . (2020). ASSIST: Evaluating the usability and performance of an indoor navigation assistant for blind and visually impaired people. Assistive Technology, 11. http://doi.org/10.1080/10400435.2020.1809553

Olmschenk, G. ., Tang, H. ., & Zhu, Z. . (2020). Improving Dense Crowd Counting Convolutional Neural Networks using Inverse k-Nearest Neighbor Maps and Multiscale Upsampling [Improving Dense Crowd Counting Convolutional Neural Networks using Inverse k-Nearest Neighbor Maps and Multiscale Upsampling]. In 15th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (Vol. 5, p. 11). http://doi.org/10.5220/0009156201850195

Olmschenk, G. ., Zhu, Z. ., & Tang, H. . (2019). Generalizing semi-supervised generative adversarial networks to regression using feature contrasting. Computer Vision and Image Understanding, 186(C), 12. http://doi.org/10.1016/j.cviu.2019.06.004

Olmschenk, G. ., Tang, H. ., & Zhu, Z. . (2018). Crowd Counting with Minimal Data Using Generative Adversarial Networks for Multiple Target Regression. In 2018 IEEE Winter Conference on Applications of Computer Vision (WACV) (p. 9). http://doi.org/10.1109/WACV.2018.00131

Gong, J. ., Feeley, C. ., Tang, H. ., Olmschenk, G. ., Nair, V. ., Zhou, Z. ., … Zhu, Z. . (2017). Building Smart and Accessible Transportation Hubs with Internet of Things, Big Data Analytics, and Affective Computing. In International Conference on Sustainable Infrastructure 2017 (p. 13). http://doi.org/10.1061/9780784481219.012