AIMC Topic: Motion Pictures
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A multimodal convolutional neuro-fuzzy network for emotion understanding of movie clips.
Neural networks : the official journal of the International Neural Network Society
Jul 2, 2019
Multimodal emotion understanding enables AI systems to interpret human emotions. With accelerated video surge, emotion understanding remains challenging due to inherent data ambiguity and diversity of video content. Although deep learning has made a ...
Does watching Han Solo or C-3PO similarly influence our language processing?
Psychological research
Apr 1, 2019
Several studies have demonstrated that perceiving an action influences the subsequent processing of action verbs. However, which characteristics of the perceived action are truly determinant to enable this influence is still unknown. The current stud...
HCF-CRS: A Hybrid Content based Fuzzy Conformal Recommender System for providing recommendations with confidence.
PloS one
Oct 9, 2018
A Recommender System (RS) is an intelligent system that assists users in finding the items of their interest (e.g. books, movies, music) by preventing them to go through huge piles of data available online. In an effort to overcome the data sparsity ...
Decoding naturalistic experiences from human brain activity via distributed representations of words.
NeuroImage
Aug 8, 2017
Natural visual scenes induce rich perceptual experiences that are highly diverse from scene to scene and from person to person. Here, we propose a new framework for decoding such experiences using a distributed representation of words. We used functi...
Box Office Forecasting considering Competitive Environment and Word-of-Mouth in Social Networks: A Case Study of Korean Film Market.
Computational intelligence and neuroscience
Jul 27, 2017
Accurate box office forecasting models are developed by considering competition and word-of-mouth (WOM) effects in addition to screening-related information. Nationality, genre, ratings, and distributors of motion pictures running concurrently with t...
Mapping between fMRI responses to movies and their natural language annotations.
NeuroImage
Jun 23, 2017
Several research groups have shown how to map fMRI responses to the meanings of presented stimuli. This paper presents new methods for doing so when only a natural language annotation is available as the description of the stimulus. We study fMRI dat...
A Personalized Electronic Movie Recommendation System Based on Support Vector Machine and Improved Particle Swarm Optimization.
PloS one
Nov 29, 2016
With the rapid development of ICT and Web technologies, a large an amount of information is becoming available and this is producing, in some instances, a condition of information overload. Under these conditions, it is difficult for a person to loca...
Precuneus functioning differentiates first-episode psychosis patients during the fantasy movie Alice in Wonderland.
Psychological medicine
Oct 25, 2016
BACKGROUND: While group-level functional alterations have been identified in many brain regions of psychotic patients, multivariate machine-learning methods provide a tool to test whether some of such alterations could be used to differentiate an ind...
Increasingly complex representations of natural movies across the dorsal stream are shared between subjects.
NeuroImage
Dec 24, 2015
Recently, deep neural networks (DNNs) have been shown to provide accurate predictions of neural responses across the ventral visual pathway. We here explore whether they also provide accurate predictions of neural responses across the dorsal visual p...
Horror Image Recognition Based on Context-Aware Multi-Instance Learning.
IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Sep 16, 2015
Horror content sharing on the Web is a growing phenomenon that can interfere with our daily life and affect the mental health of those involved. As an important form of expression, horror images have their own characteristics that can evoke extreme e...
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