scholarly journals Multimodal Classification of Stressful Environments in Visually Impaired Mobility Using EEG and Peripheral Biosignals

2019 ◽  
pp. 1-1 ◽  
Author(s):  
Charalampos Saitis ◽  
Kyriaki Kalimeri
Keyword(s):  
Visually Impaired ◽  
Impaired Mobility ◽  
Multimodal Classification ◽  
Stressful Environments

Indoor Navigation Aid Systems for the Blind and Visually Impaired Based on Depth Sensors

2021 ◽  
pp. 187-223
Author(s):  
Fernando Merchan ◽  
Martin Poveda ◽  
Danilo E. Cáceres-Hernández ◽  
Javier E. Sanchez-Galan
Keyword(s):  
Deep Learning ◽  
Visually Impaired ◽  
Indoor Navigation ◽  
Assistive Technologies ◽  
Microsoft Kinect ◽  
Depth Sensors ◽  
Blind And Visually Impaired ◽  
Recent Developments ◽  
Depth Vision

This chapter focuses on the contributions made in the development of assistive technologies for the navigation of blind and visually impaired (BVI) individuals. A special interest is placed on vision-based systems that make use of image (RGB) and depth (D) information to assist their indoor navigation. Many commercial RGB-D cameras exist on the market, but for many years the Microsoft Kinect has been used as a tool for research in this field. Therefore, first-hand experience and advances on the use of Kinect for the development of an indoor navigation aid system for BVI individuals is presented. Limitations that can be encountered in building such a system are addressed at length. Finally, an overview of novel avenues of research in indoor navigation for BVI individuals such as integration of computer vision algorithms, deep learning for the classification of objects, and recent developments with stereo depth vision are discussed.

scholarly journals Multimodal Classification of EEG During Physical Activity

2019 ◽  
Author(s):  
Yi Ding ◽  
Brandon Huynh ◽  
Aiwen Xu ◽  
Tom Bullock ◽  
Hubert Cecotti ◽  
...  
Keyword(s):  
Physical Activity ◽  
Multimodal Classification

scholarly journals Multimodal Object Classification Models Inspired by Multisensory Integration in the Brain

2019 ◽  
Vol 9 (1) ◽  
pp. 3 ◽  
Author(s):  
Rajesh Amerineni ◽  
Resh S. Gupta ◽  
Lalit Gupta
Keyword(s):  
Multisensory Integration ◽  
Object Classification ◽  
Classification Systems ◽  
Multilayer Perceptrons ◽  
Classification Models ◽  
Multivariate Statistical ◽  
Statistical Classifiers ◽  
Multimodal Classification ◽  
The Brain

Two multimodal classification models aimed at enhancing object classification through the integration of semantically congruent unimodal stimuli are introduced. The feature-integrating model, inspired by multisensory integration in the subcortical superior colliculus, combines unimodal features which are subsequently classified by a multimodal classifier. The decision-integrating model, inspired by integration in primary cortical areas, classifies unimodal stimuli independently using unimodal classifiers and classifies the combined decisions using a multimodal classifier. The multimodal classifier models are implemented using multilayer perceptrons and multivariate statistical classifiers. Experiments involving the classification of noisy and attenuated auditory and visual representations of ten digits are designed to demonstrate the properties of the multimodal classifiers and to compare the performances of multimodal and unimodal classifiers. The experimental results show that the multimodal classification systems exhibit an important aspect of the “inverse effectiveness principle” by yielding significantly higher classification accuracies when compared with those of the unimodal classifiers. Furthermore, the flexibility offered by the generalized models enables the simulations and evaluations of various combinations of multimodal stimuli and classifiers under varying uncertainty conditions.

Multimodal Classification of Breast Masses in Mammography and MRI Using Unimodal Feature Selection and Decision Fusion

2012 ◽  
pp. 88-95
Author(s):  
Jan M. Lesniak ◽  
Guido van Schie ◽  
Christine Tanner ◽  
Bram Platel ◽  
Henkjan Huisman ◽  
...  
Keyword(s):  
Feature Selection ◽  
Decision Fusion ◽  
Breast Masses ◽  
Multimodal Classification
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