no code implementations • 2 Nov 2022 • Zhong Zhuang, David Yang, Felix Hofmann, David Barmherzig, Ju Sun
Phase retrieval (PR) concerns the recovery of complex phases from complex magnitudes.
1 code implementation • 2 Dec 2021 • Zihang Meng, David Yang, Xuefei Cao, Ashish Shah, Ser-Nam Lim
Our work in this paper overcomes this by harvesting objects corresponding to a given sentence from the training set, even if they don't belong to the same image.
no code implementations • 29 Sep 2021 • Sethuraman Sankaran, David Yang, Ser-Nam Lim
Tasks that rely on multi-modal information typically include a fusion module that combines information from different modalities.
no code implementations • 9 Jun 2021 • Kshitij Tayal, Raunak Manekar, Zhong Zhuang, David Yang, Vipin Kumar, Felix Hofmann, Ju Sun
Several deep learning methods for phase retrieval exist, but most of them fail on realistic data without precise support information.
no code implementations • 8 Apr 2021 • Sethuraman Sankaran, David Yang, Ser-Nam Lim
In this work, we develop a Refiner Fusion Network (ReFNet) that enables fusion modules to combine strong unimodal representation with strong multimodal representations.
no code implementations • 16 Nov 2020 • Li Chen, David Yang, Purvi Goel, Ilknur Kabul
This paper proposes CANC, a Co-teaching Active Noise Cancellation method, applied in spatial computing to address deep learning trained with extreme noisy labels.
no code implementations • 31 Oct 2020 • Parikha Mehrotra, David Yang, Scott Weigand, Shreyas Sen
However, there is a gap in the knowledge about the mechanism and sources of interference in this region (crucial in allowing for proper choice of data transmission band).
no code implementations • 29 Oct 2020 • Arunashish Datta, Mayukh Nath, David Yang, Shreyas Sen
FEM based simulation results are used to analyze the channel response of human body for different positions and sizes of the device which are further verified using measurement results to validate the developed biophysical model.