Results 21 to 30 of about 43,272 (165)
BMC Oral Health, 2022 Background Ensuring high accuracy in multimodal image fusion for oral and maxillofacial tumors is crucial before further application. The aim of this study was to explore the factors influencing the accuracy of multimodal image fusion for oral and ...
Lei-Hao Hu +5 more
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Progressive Fusion for Multimodal Integration
CoRR, 2022 Integration of multimodal information from various sources has been shown to boost the performance of machine learning models and thus has received increased attention in recent years. Often such models use deep modality-specific networks to obtain unimodal features which are combined to obtain "late-fusion" representations.
Shiv Shankar +2 more
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Hierarchical Multimodal Fusion for Ground-Based Cloud Classification in Weather Station Networks
IEEE Access, 2019 Recently, the multimodal information is taken into consideration for ground-based cloud classification in weather station networks, but intrinsic correlations between the multimodal information and the visual information cannot be mined sufficiently.
Shuang Liu +3 more
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Multimodal Fusion Refiner Networks
CoRR, 2021 Tasks that rely on multi-modal information typically include a fusion module that combines information from different modalities. In this work, we develop a Refiner Fusion Network (ReFNet) that enables fusion modules to combine strong unimodal representation with strong multimodal representations.
Sethuraman Sankaran +2 more
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Sparse Fusion for Multimodal Transformers
, 2022 Multimodal classification is a core task in human-centric machine learning.We observe that information is highly complementary across modalities, thus unimodal information can be drastically sparsified prior to multimodal fusion without loss of accuracy.To this end, we present Sparse Fusion Transformers (SFT), a novel multimodal fusion method for ...
Helen Bear +7 more
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Multimodal partial estimates fusion [PDF]
2009 IEEE 12th International Conference on Computer Vision, 2009 Fusing partial estimates is a critical and common problem in many computer vision tasks such as part-based detection and tracking. It generally becomes complicated and intractable when there are a large number of multimodal partial estimates, and thus it is desirable to find an effective and scalable fusion method to integrate these partial estimates ...
Jiang Xu 0002 +2 more
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Brain tumor segmentation in multimodal MRI via pixel-level and feature-level image fusion
Frontiers in Neuroscience, 2022 Brain tumor segmentation in multimodal MRI volumes is of great significance to disease diagnosis, treatment planning, survival prediction and other relevant tasks.
Yu Liu +8 more
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Advancing healthcare through multimodal data fusion: a comprehensive review of techniques and applications [PDF]
PeerJ Computer ScienceWith the increasing availability of diverse healthcare data sources, such as medical images and electronic health records, there is a growing need to effectively integrate and fuse this multimodal data for comprehensive analysis and decision-making ...
Jing Ru Teoh +5 more
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Performance Evaluation of Multimodal Multifeature Authentication System Using KNN Classification
The Scientific World Journal, 2015 This research proposes a multimodal multifeature biometric system for human recognition using two traits, that is, palmprint and iris. The purpose of this research is to analyse integration of multimodal and multifeature biometric system using feature ...
Gayathri Rajagopal +1 more
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Challenges In Multimodal Data Fusion
, 2014 Publication in the conference proceedings of EUSIPCO, Lisbon, Portugal ...
Lahat, Dana +2 more
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