Zobrazeno 1 - 10
of 19
pro vyhledávání: '"Andre Van Rynbach"'
Publikováno v:
Liquid Crystals XXVI.
Autor:
Theus H. Aspiras, Vijayan K. Asari, Nina Singer, Jonathan Schierl, Andy Stokes, Brett Keaffaber, Andre Van Rynbach, Kevin Decker, David Rabb
Publikováno v:
Pattern Recognition and Tracking XXXIII.
Publikováno v:
SID Symposium Digest of Technical Papers. 52:402-405
Autor:
Nina M. Singer, Vijayan K. Asari, Theus Aspiras, Jonathan Schierl, Andrew Stokes, Brett Keaffaber, Andre Van Rynbach, Kevin Decker, David J. Rabb
Publikováno v:
Geospatial Informatics XII.
Autor:
Jonathan Schierl, Vijayan Asari, Nina Singer, Theus Aspiras, Andrew Stokes, Brett Keaffaber, Andre Van Rynbach, Kevin Decker, David Rabb
Publikováno v:
Multimodal Image Exploitation and Learning 2022.
Autor:
Joshua A. Burrow, Andre Van Rynbach, Piyush Shah, Jonathan R. Thompson, Jonathan E. Slagle, Matthew S. Mills, John Demis, Ning Cao, Ray Secondo, Mulaine Shih, Eric S. Harper, Imad Agha
Publikováno v:
Advanced Optics for Imaging Applications: UV through LWIR VII.
Autor:
Jonathan Schierl, Vijayan Asari, Nina Singer, Theus Aspiras, Andrew Stokes, Brett Keaffaber, Andre Van Rynbach, Kevin Decker, David Rabb
Publikováno v:
2021 IEEE Applied Imagery Pattern Recognition Workshop (AIPR).
Autor:
Nina Singer, Vijayan K. Asari, Theus Aspiras, Jonathan Schierl, Andrew Stokes, Brett Keaffaber, Andre Van Rynbach, Kevin Decker, David Rabb
Publikováno v:
2021 IEEE Applied Imagery Pattern Recognition Workshop (AIPR).
Publikováno v:
Emerging Liquid Crystal Technologies XVI.
There has been an increasing demand for fast and efficient random access pointing within emerging applications such as LiDAR, space based optical communications, displays, and autonomous vehicles. Particularly, Electro-Optical beam steering approache
Autor:
Quinn Graehling, Theus H. Aspiras, Dave Rabb, Vijay Asari, Jonathan Schierl, Andre Van Rynbach
Publikováno v:
AIPR
Multi-modal data is useful for complex imaging scenarios due to the exclusivity of information found in each modality, but there is a lack of meaningful comparisons of different modalities for object detection. In our work, we propose three contribut