136 citations · 140 across the 6 of their papers we have counts for
7 papers
Shadow Augmentation for Handwashing Action Recognition: from Synthetic to Real Datasets
Shengtai Ju, Amy R. Reibman
Video analytics systems designed for deployment in outdoor conditions can be vulnerable to many environmental changes, particularly changes in shadow. Existing works have shown tha…
Exploring the Impact of Hand Pose and Shadow on Hand-washing Action Recognition
Shengtai Ju, Amy R. Reibman
In the real world, camera-based application systems can face many challenges, including environmental factors and distribution shift. In this paper, we investigate how pose and sha…
Turkey Behavior Identification System with a GUI Using Deep Learning and Video Analytics
Shengtai Ju, Sneha Mahapatra, Marisa A. Erasmus +2
In this paper, we propose a video analytics system to identify the behavior of turkeys. Turkey behavior provides evidence to assess turkey welfare, which can be negatively impacted…
Ensemble Wrapper Subsampling for Deep Modulation Classification
Sharan Ramjee, Shengtai Ju, Diyu Yang +3
Subsampling of received wireless signals is important for relaxing hardware requirements as well as the computational cost of signal processing algorithms that rely on the output s…
Efficient Training of Deep Classifiers for Wireless Source Identification using Test SNR Estimates
Xingchen Wang, Shengtai Ju, Xiwen Zhang +2
We study efficient deep learning training algorithms that process received wireless signals, if a test Signal to Noise Ratio (SNR) estimate is available. We focus on two tasks that…
Deep Learning for Interference Identification: Band, Training SNR, and Sample Selection
Xiwen Zhang, Tolunay Seyfi, Shengtai Ju +3
We study the problem of interference source identification, through the lens of recognizing one of 15 different channels that belong to 3 different wireless technologies: Bluetooth…
Fast Deep Learning for Automatic Modulation Classification
Sharan Ramjee, Shengtai Ju, Diyu Yang +3
In this work, we investigate the feasibility and effectiveness of employing deep learning algorithms for automatic recognition of the modulation type of received wireless communica…