scholarly journals Multimodal Classification of Mangoes

2019 ◽  
Author(s):  
Son V.T. Dao
Keyword(s):  
Multimodal Classification

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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