activity
20202023
most citedContinual Learning in Sensor-based Human Activity Recognition: an Empirical Benchmark Analysis

66 citations · 134 across the 6 of their papers we have counts for

collaborators

6 papers

cs.SD2023

Towards Automated Animal Density Estimation with Acoustic Spatial Capture-Recapture

Yuheng Wang, Juan Ye, David L. Borchers

Passive acoustic monitoring can be an effective way of monitoring wildlife populations that are acoustically active but difficult to survey visually. Digital recorders allow survey…

cs.HC2023★ 41 cited

An End-to-End Review of Gaze Estimation and its Interactive Applications on Handheld Mobile Devices

Yaxiong Lei, Shijing He, Mohamed Khamis +1

In recent years we have witnessed an increasing number of interactive systems on handheld mobile devices which utilise gaze as a single or complementary interaction modality. This…

cs.HC2023★ 16 cited

DynamicRead: Exploring Robust Gaze Interaction Methods for Reading on Handheld Mobile Devices under Dynamic Conditions

Yaxiong Lei, Yuheng Wang, Tyler Caslin +4

Enabling gaze interaction in real-time on handheld mobile devices has attracted significant attention in recent years. An increasing number of research projects have focused on sop…

cs.CV2022

A simple normalization technique using window statistics to improve the out-of-distribution generalization on medical images

Chengfeng Zhou, Songchang Chen, Chenming Xu +6

Since data scarcity and data heterogeneity are prevailing for medical images, well-trained Convolutional Neural Networks (CNNs) using previous normalization methods may perform poo…

eess.SP2021★ 66 cited

Continual Learning in Sensor-based Human Activity Recognition: an Empirical Benchmark Analysis

Saurav Jha, Martin Schiemer, Franco Zambonelli +1

Sensor-based human activity recognition (HAR), i.e., the ability to discover human daily activity patterns from wearable or embedded sensors, is a key enabler for many real-world a…

cs.LG2020★ 11 cited

Continual Learning in Human Activity Recognition: an Empirical Analysis of Regularization

Saurav Jha, Martin Schiemer, Juan Ye

Given the growing trend of continual learning techniques for deep neural networks focusing on the domain of computer vision, there is a need to identify which of these generalizes…