no code implementations • 25 Sep 2023 • Chiao-Yi Wang, Faranguisse Kakhi Sadrieh, Yi-Ting Shen, Shih-En Chen, Sarah Kim, Victoria Chen, Achyut Raghavendra, Dongyi Wang, Osamah Saeedi, Yang Tao
To fill this gap, we establish MEMO, the first public multimodal EMA and OCTA retinal image dataset.
no code implementations • CVPR 2023 • Yi-Ting Shen, Hyungtae Lee, Heesung Kwon, Shuvra Shikhar Bhattacharyya
To effectively interrogate UAV-based images for detecting objects of interest, such as humans, it is essential to acquire large-scale UAV-based datasets that include human instances with various poses captured from widely varying viewing angles.
no code implementations • 31 Aug 2022 • Yi-Ting Shen, Yaesop Lee, Heesung Kwon, Damon M. Conover, Shuvra S. Bhattacharyya, Nikolas Vale, Joshua D. Gray, G. Jeremy Leong, Kenneth Evensen, Frank Skirlo
Learning to detect objects, such as humans, in imagery captured by an unmanned aerial vehicle (UAV) usually suffers from tremendous variations caused by the UAV's position towards the objects.
no code implementations • ICCV 2019 • Keng-Chi Liu, Yi-Ting Shen, Jan P. Klopp, Liang-Gee Chen
Our proposed two-stage integration more than halves the gap towards fully supervised methods when compared to previous state-of-the-art in transfer learning.