We propose a late fusion mechanism of multiple rankings to combine the results from several uni-modal searches in Sentinel 2 image collections. We fist create a K-order tensor from the results of separate searches by visual features, concepts, spatial and temporal information. Visual concepts and...
Our proposed approach can be seen as a novel data fusion method based on tensor representation. Indeed, the histograms of different local descriptors extracted from both 2D and 3D face modalities are combined through different tensor modes. The extensive experimental evaluation carried out on FRGC v...
By synergistically integrating multimodal aerosol data acquired from diverse sources via a tensor-flow-based data fusion method, a gap-free aerosol optical depth (AOD) dataset with a daily 1 km resolution covering the period of 2000–2020 in China was generated. Specifically, data gaps in ...
We benchmarked the performance of the proposed multimodal prediction model with respect to the state-of-the-art medical fusion techniques. 2 Literature review EHR contains a plethora of both structured data such as 1) Numerical quantities: patient demographics, clinical lab results like body mass in...
However, it imposes a big challenge to explore smart data from big data gathered from smart city with various advanced fusion and analysis approaches. This paper proposes an incremental tensor-based fuzzy c-means approach (IT-FCM) for obtaining smart data from continuously generated big data. ...
(STP-MFM) pooling method for sentiment analysis. The proposed MFM pooling improves the fusion efficiency of multiple modalities for various sentiment analysis tasks. Similarly, the introduction of STP allows the connection of two factors with different dimensionality. The main contributions of this ...
LSJAK Houthuys - 《Information Fusion》 被引量: 0发表: 2021年 TPpred-ATMV: therapeutic peptide prediction by adaptive multi-view tensor learning model MOTIVATION. Therapeutic peptide prediction is important for the discovery of efficient therapeutic peptides and drug development. Researchers have devel...
multimodal face data fusionN-dimensional PCAIn this paper, a novel feature representation to multimodal face recognition is proposed, which possesses three properties: completeness, robustness and compactness. This feature descriptor allows all information of an object to be reproduced and its ...
Furthermore, to fuse cloud visual tensor and multimodal tensor, we propose the tensor fusion layer to exploit the high-order correlations between them. The DTFN is evaluated on MGCD and exceeds the state-of-the-art methods, which validates its effectiveness for multimodal ground-based cloud ...
image fusionstructure tensortraceeignevalueIn this paper, a structure tensor based approach is proposed for multi-focus image fusion within the wavelet framework. Structure tensor is employed to extract local features in detail sub-bands. A nonlinear flow based on the trace of the struc...