Search Results for author: David Yang

Found 7 papers, 0 papers with code

Object-Centric Unsupervised Image Captioning

no code implementations2 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.

Image Captioning

Refining Multimodal Representations using a modality-centric self-supervised module

no code implementations29 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.

Few-Shot Learning

Phase Retrieval using Single-Instance Deep Generative Prior

no code implementations9 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.

Multimodal Fusion Refiner Networks

no code implementations8 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.

Robust Deep Learning with Active Noise Cancellation for Spatial Computing

no code implementations16 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.

In-The-Wild Interference Characterization and Modelling for Electro-Quasistatic-HBC with Miniaturized Wearables

no code implementations31 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).

Advanced Biophysical Model to Capture Channel Variability for EQS Capacitive HBC

no code implementations29 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.

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