From data fusion to knowledge fusion [PDF]
Proceedings of the VLDB Endowment, 2014 The task of data fusion is to identify the true values of data items ( e.g. , the true date of birth for Tom Cruise ) among multiple observed values drawn from different sources ( e.g. , Web sites) of varying (and unknown) reliability.
Wilko Horn +6 more
openaire +6 more sources
BEVFusion: Multi-Task Multi-Sensor Fusion with Unified Bird's-Eye View Representation [PDF]
IEEE International Conference on Robotics and Automation, 2022 Multi-sensor fusion is essential for an accurate and reliable autonomous driving system. Recent approaches are based on point-level fusion: augmenting the LiDAR point cloud with camera features.
Zhijian Liu +6 more
semanticscholar +1 more source
LRRNet: A Novel Representation Learning Guided Fusion Network for Infrared and Visible Images [PDF]
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2023 Deep learning based fusion methods have been achieving promising performance in image fusion tasks. This is attributed to the network architecture that plays a very important role in the fusion process.
Hui Li +4 more
semanticscholar +1 more source
CDDFuse: Correlation-Driven Dual-Branch Feature Decomposition for Multi-Modality Image Fusion [PDF]
Computer Vision and Pattern Recognition, 2022 Multi-modality (MM) image fusion aims to render fused images that maintain the merits of different modalities, e.g., functional highlight and detailed textures.
Zixiang Zhao +7 more
semanticscholar +1 more source
Status of the ITER ECRH&CD control system development [PDF]
EPJ Web of Conferences, 2023 The ITER ECRH&CD system is designed to inject 20 MW of millimetre-wave at 170 GHz into the vacuum vessel. The system is composed of many sub-systems, namely High-Voltage Power Supplies (HVPS), Gyrotrons, Transmission Lines (TL), Ex-vessel Waveguides (EW),
Carannante Giuseppe +6 more
doaj +1 more source
Multi-Modal Fusion Transformer for End-to-End Autonomous Driving [PDF]
Computer Vision and Pattern Recognition, 2021 How should representations from complementary sensors be integrated for autonomous driving? Geometry-based sensor fusion has shown great promise for perception tasks such as object detection and motion forecasting.
Aditya Prakash +2 more
semanticscholar +1 more source
Improving Multimodal Fusion with Hierarchical Mutual Information Maximization for Multimodal Sentiment Analysis [PDF]
Conference on Empirical Methods in Natural Language Processing, 2021 In multimodal sentiment analysis (MSA), the performance of a model highly depends on the quality of synthesized embeddings. These embeddings are generated from the upstream process called multimodal fusion, which aims to extract and combine the input ...
Wei Han, Hui Chen, Soujanya Poria
semanticscholar +1 more source
Differentiating multi-MeV, multi-ion spectra with CR-39 solid-state nuclear track detectors
Scientific Reports, 2023 The development of high intensity petawatt lasers has created new possibilities for ion acceleration and nuclear fusion using solid targets. In such laser-matter interaction, multiple ion species are accelerated with broad spectra up to hundreds of MeV ...
M. S. Schollmeier +20 more
doaj +1 more source
Preceding propagation of turbulence pulses at avalanche events in a magnetically confined plasma
Scientific Reports, 2022 The preceding propagation of turbulence pulses has been observed for the first time in heat avalanche events during the collapse of the electron internal transport barrier (e-ITB) in the Large Helical Device.
N. Kenmochi +10 more
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Deep Learning in Multimodal Remote Sensing Data Fusion: A Comprehensive Review [PDF]
International Journal of Applied Earth Observation and Geoinformation, 2022 With the extremely rapid advances in remote sensing (RS) technology, a great quantity of Earth observation (EO) data featuring considerable and complicated heterogeneity is readily available nowadays, which renders researchers an opportunity to tackle ...
Jiaxin Li +6 more
semanticscholar +1 more source