The proliferation of fake news and its serious negative social influence push detection methods to become necessary tools for web managers. Meanwhile, the multi-media nature media makes multi-modal popular ability capture more modal features than uni-modal methods. However, current literature on is likely pursue accuracy but ignore robustness (the in case abnormality malicious attack) detector....

hris Harding is an assistant professor at Iowa State University’s Human-computerinteraction program and is interested in designing multi-modal interfaces for geoscientists. In his presentation, he will share some of the experiences of working with geoscientific Virtual Environments and multi-modal interfaces over the last years and talk about the opportunities and challenges of increasing the u...

An object model of multi-modal transport networks is developed with particular emphasis on applications in trip planning. The model caters for both public and private transport modes, and incorporates spatial and temporal data. A uniform approach to optimum trip nding across multi-modal transport networks is developed. The multi-modal network is spatially ordered using a quadtree storage object...

We introduce Multi-Modal Utility Trees (MMU), an algorithm for autonomously learning decision treebased state abstractions in Partially Observable Markov Decision Processes with multi-modal observations. MMU builds the trees using the Kolmogorov-Smirnov statistical test. Additionally, MMU incorporates the ability to perform online tree restructuring, enabling it to build and maintain a compact ...

This paper investigates audio-visual interaction, i.e. inter-modal influences, in linear-regressive model adaptation for multi-modal speech recognition. In the multi-modal adaptation, inter-modal information may contribute the performance of speech recognition. Thus the influence and advantage of intermodal elements should be examined. Experiments were conducted to evaluate several transformati...

in treating the subject of musical language, a persian musician would be intrinsically drawn to the structural similarities between the persian music and language. indeed persian music and language are extremely related in their metrics, intonations and structural phrases (syntax). although we will draw upon this relationship, our aim in this article is to present “music as a language,” consist...

Multi-modal semantics has relied on feature norms or raw image data for perceptual input. In this paper we examine grounding semantic representations in raw auditory data, using standard evaluations for multi-modal semantics, including measuring conceptual similarity and relatedness. We also evaluate cross-modal mappings, through a zero-shot learning task mapping between linguistic and auditory...

Multi-modal imaging systems have recently been drawing attention in fields such as medical imaging, remote sensing and video surveillance systems. In such systems, estimating depth has become possible due to promising progress of multi-modal matching techniques. In this article, we perform a systematic performance evaluation of similarity measures frequently used in the literature for dense mul...

Multi-modal techniques have received increasing interest in the neuroscientific and brain computer interface (BCI) communities in recent times. Two aspects of multi-modal imaging for BCI will be reviewed. First, the use of recordings of multiple subjects to help find subject-independent BCI classifiers is considered. Then, multi-modal neuroimaging methods involving combined electroencephalogram...