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Multi-modal identity verification using expert fusion
Information Fusion, 2000The contribution of this paper is to compare paradigms coming from the classes of parametric, and non-parametric techniques to solve the decision fusion problem encountered in the design of a multi-modal biometrical identity verification system. The multimodal identity verification system under consideration is built of d modalities in parallel, each ...
Patrick Verlinde +2 more
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Self-supervised multi-modal fusion network for multi-modal thyroid ultrasound image diagnosis
Computers in Biology and Medicine, 2022Ultrasound is a typical non-invasive diagnostic method often used to detect thyroid cancer lesions. However, due to the limitations of the information provided by ultrasound images, shear wave elastography (SWE) and color doppler ultrasound (CDUS) are also used clinically to assist in diagnosis, which makes the diagnosis time-consuming, labor-intensive,
Zhuo Xiang +7 more
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The 12th IEEE International Conference on Fuzzy Systems, 2003. FUZZ '03., 2004
Clustering groups items together that are most similar to each other and sets those that are least similar into different clusters. Methods have been developed to cluster records in a data set that are of only qualitative or quantitative data. Data sets exist that contain a mix of qualitative (nominal and ordinal) and quantitative (discrete and ...
S. Coppock, L. Mazlack
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Clustering groups items together that are most similar to each other and sets those that are least similar into different clusters. Methods have been developed to cluster records in a data set that are of only qualitative or quantitative data. Data sets exist that contain a mix of qualitative (nominal and ordinal) and quantitative (discrete and ...
S. Coppock, L. Mazlack
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Multi-modal fusion for video understanding
Proceedings 30th Applied Imagery Pattern Recognition Workshop (AIPR 2001). Analysis and Understanding of Time Varying Imagery, 2002The exploitation of semantic information in computer vision problems can be difficult because of the large difference in representations and levels of knowledge. Image analysis is formulated in terms of low-level features describing image structure and intensity, while high-level knowledge such as purpose and common sense are encoded in abstract, non ...
A. Hoogs, J. Mundy, G. Cross
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Tracking Humans using Multi-modal Fusion
2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Workshops, 2006Human motion detection plays an important role in automated surveillance systems. However, it is challenging to detect non-rigid moving objects (e.g. human) robustly in a cluttered environment. In this paper, we compare two approaches for detecting walking humans using multi-modal measurements- video and audio sequences.
null Xiaotao Zou, B. Bhanu
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Describing Videos using Multi-modal Fusion
Proceedings of the 24th ACM international conference on Multimedia, 2016Describing videos with natural language is one of the ultimate goals of video understanding. Video records multi-modal information including image, motion, aural, speech and so on. MSR Video to Language Challenge provides a good chance to study multi-modality fusion in caption task. In this paper, we propose the multi-modal fusion encoder and integrate
Qin Jin +4 more
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Multi Modal Image Fusion: Comparative Analysis
2019 International Conference on Communication and Signal Processing (ICCSP), 2019Image fusion acts as a powerful tool in the medical domain. It is an essential method for enhancing the quality of images by combining the complementary images which are captured from various sensors or cameras. The aim of multi modal image fusion technique is to obtain a single fused image by fusing the images of different modalities.
Harpreet Kaur +2 more
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Commuting Conditional GANS for Multi-Modal Fusion
ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2020This paper presents a data driven approach to multi-modal fusion where a hidden latent sub-space between the different modalities is learned. The hidden space is estimated via a bank of Conditional GANs which also commute with each other, leading to an output that lies in a common subspace.
Siddharth Roheda +2 more
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Diffusion-driven multi-modality medical image fusion
Medical & Biological Engineering & ComputingMulti-modality medical image fusion (MMIF) technology utilizes the complementarity of different modalities to provide more comprehensive diagnostic insights for clinical practice. Existing deep learning-based methods often focus on extracting the primary information from individual modalities while ignoring the correlation of information distribution ...
Jiantao, Qu +4 more
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On Multi-modal Fusion Learning in constraint propagation
Information Sciences, 2018zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Li, Yaoyi, Lu, Hongtao
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