Titlebook: Intelligent Human Computer Interaction; 8th International Co Anupam Basu,Sukhendu Das,Samit Bhattacharya Conference proceedings 2017 Spring

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过份

Sreeja S.R.,Vaidic Joshi,Shabnam Samima,Anushri Saha,Joytirmoy Rabha,Baljeet Singh Cheema,Debasis Sa

Accommodation

Abhishek Mahata,Nandini Saini,Sneha Saharawat,Ritu Tiwari

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WAX

Resign

玷污

BCI Augmented Text Entry Mechanism for People with Special Needsn of feature set to make the interface work efficiently. The results of five able-bodied users show that the error rate per minute is significantly reduced and it also illustrates that it can be further used to develop better BCI augmented HCI systems.

MUTE

A Comparative Study of Classifier Performance on Spatial and Temporal Features of Handwritten Behaviinatory information in deception detection. In this work, a set of total twelve features (spatial and temporal with pressure measures) features were used from online handwritten data. Five different classifiers (Naïve Bayes, Logistic Regression, Multi-Layer Perceptron, Random Forest and Support Vect

FIS

Estimation of Mental Fatigue During EEG Based Motor Imagery these EEG oscillatory rhythm fluctuations to model EEG-fatigue relationships. A statistical classifier is used to model EEG-fatigue relationship accurately. With Kernel Partial Least Square output we track the growth of mental fatigue with time.