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20172020
most citedGender and Emotion Recognition with Implicit User Signals

4 citations · 5 across the 3 of their papers we have counts for

collaborators

5 papers

cs.HC20201 cited

Gender and Emotion Recognition from Implicit User Behavior Signals

Maneesh Bilalpur, Seyed Mostafa Kia, Mohan Kankanhalli +1

This work explores the utility of implicit behavioral cues, namely, Electroencephalogram (EEG) signals and eye movements for gender recognition (GR) and emotion recognition (ER) fr…

cs.HC2018

Investigating the generalizability of EEG-based Cognitive Load Estimation Across Visualizations

Viral Parekh, Maneesh Bilalpur, Sharavan Kumar +3

We examine if EEG-based cognitive load (CL) estimation is generalizable across the character, spatial pattern, bar graph and pie chart-based visualizations for the nback~task. CL i…

cs.HC2018

EEG-based Evaluation of Cognitive Workload Induced by Acoustic Parameters for Data Sonification

Maneesh Bilalpur, Mohan Kankanhalli, Stefan Winkler +1

Data Visualization has been receiving growing attention recently, with ubiquitous smart devices designed to render information in a variety of ways. However, while evaluations of v…

cs.HC20174 cited

Gender and Emotion Recognition with Implicit User Signals

Maneesh Bilalpur, Seyed Mostafa Kia, Manisha Chawla +2

We examine the utility of implicit user behavioral signals captured using low-cost, off-the-shelf devices for anonymous gender and emotion recognition. A user study designed to exa…

cs.HC2017

Discovering Gender Differences in Facial Emotion Recognition via Implicit Behavioral Cues

Maneesh Bilalpur, Seyed Mostafa Kia, Tat-Seng Chua +1

We examine the utility of implicit behavioral cues in the form of EEG brain signals and eye movements for gender recognition (GR) and emotion recognition (ER). Specifically, the ex…