The aim of this paper is to demonstrate how behavior patterns and related anomalies comprehensively define a CPS. Tensor decompositions are hypothesized as the solution in the context of multimodal smart-grid-originated Big Data analysis. Tensorial data representation is demonstrated to capture the ...
Multi-Feature Fusion for Multimodal Attentive Sentiment Analysis Sentiment analysis has been an interesting and challenging task, researchers mostly pay attention to single-modal (image or text) emotion recognition, less attention is paid to joint analysis of multi-modal data. Most existing multi-moda...
Multimodal random forest based tensor regression 喜欢 0 阅读量: 79 作者:S Kaymak,I Patras 摘要: This study presents a method, called random forest based tensor regression, for real-time head pose estimation using both depth and intensity data. The method builds on random forests and proposes ...
which learns both such dynamics end-to-end. The proposedapproach is tailored for the volatile nature of spoken language in onlinevideos as well as accompanying gestures and voice. In the experiments, ourmodel outperforms state-of-the-art approaches for both multimodal and unimodalsentiment analysis...
In multimedia field, several network-based learning models have been employed to fuse the information of intra-modality and inter-modality [23], [24], and the tensor fusion network is proposed for multimodal sentiment analysis [43]. The current development of LRTR can be classified into two ...
Multilinear discriminant analysis (MDA)Dimensionality reductionSubspace tensorFusion 2D-3D modalitiesIn the last few years, there is a growing interest in multilinear subspace learning for dimensionality reduction of multidimensional data. In this paper, we proposed a multimodal 2D + 3D face verification ...
"Tensor fusion network for multimodal sentiment analysis." EMNLP 2017 Oral. It requires PyTorch and the CMU Multimodal Data SDK (https://github.com/A2Zadeh/CMU-MultimodalDataSDK) to function properly. The training data (CMU-MOSI dataset) will be automatically downloaded if you run the script ...
Zadeh, Amir, et al. "Tensor fusion network for multimodal sentiment analysis." EMNLP 2017 Oral. It requires PyTorch and the CMU Multimodal Data SDK (https://github.com/A2Zadeh/CMU-MultimodalDataSDK) to function properly. The training data (CMU-MOSI dataset) will be automatically downloaded if...
Developing a big data analytics framework for generating the Long-term Gap-free High-resolution Air Pollutant concentration dataset (abbreviated as LGHAP) is of great significance for environmental management and Earth system science analysis. By synergistically integrating multimodal aerosol data acquired ...
Multimodal information including single-cell epigenomics52 or proteomics data53 can also be incorporated in the multistable dynamical system to enhance the transition tensor calculation. The automatic detection of root and target states in multistable models is always challenging, and the previous knowledge...