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Alzheimer’s disease diagnosis via multimodal feature fusion
Computers in Biology and Medicine, 2022Alzheimer's disease (AD) is the most common neurodegenerative disorder in the elderly. Early diagnosis of AD plays a vital role in slowing down the progress of AD because there is no effective drug to treat the disease. Some deep learning models have recently been presented for AD diagnosis and have more satisfactory performance than classic machine ...
Yue, Tu +4 more
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Multi-feature fusion deep networks
Neurocomputing, 2016In this paper, we propose a novel deep networks, multi-feature fusion deep networks (MFFDN), based on denoising autoencoder. MFFDN significantly reduces the classification error while giving the interpretability of the hidden-layer feature representation in learning process.
Gang Ma, Xi Yang, Bo Zhang, Zhongzhi Shi
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Contour feature fusion SSD Algorithm
2019 Chinese Control Conference (CCC), 2019Aiming at the missed detection problem in Single Shot MultiBox Detector (SSD), this paper proposes Contour feature fusion SSD algorithm (C-SSD). The algorithm performs fusion operation on the features layer to complement the object contour, improve expression ability of object feature information. This operation can enhance the detection capability and
Dawei Yang +3 more
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Brain Tumor Classification: Feature Fusion
2019 International Conference on Computer and Information Sciences (ICCIS), 2019Brain tumor detection is a challenging task in medical image analysis. The manual process performs through domain specialists is a more time-consuming task. Numerous works are represented for brain tumor detection and discrimination but still, there is a need for a fast and efficient technique.
Javeria Amin +4 more
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Intact and deficient feature fusion in schizophrenia
European Archives of Psychiatry and Clinical Neuroscience, 2005In patients with schizophrenia, early as well as late stages of information processing can be deficient. Therefore, it is important to determine the earliest occurrences of aberrant processing since deficits on these stages may cause abnormal processing on later, e. g. cognitive, levels.
Andreas, Brand +4 more
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Person recognition by feature fusion
2011 International Conference on Computer Science and Service System (CSSS), 2011Biometric fusion is an essential procedure in any multi-modal biometric person recognition systems and it can be performed at sensor, feature, score and decision levels. This paper proposes a simulated annealing (SA) algorithm for the fusion of multi-modal biometric data.
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Fusion of Extended Fingerprint Features
2020Extended fingerprint features such as pores, dots and incipient ridges have attracted increasing attention from researchers and engineers working on automatic fingerprint recognition systems. A variety of methods have been proposed to combine these features with the traditional minutiae features.
Feng Liu, Qijun Zhao, David Zhang
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Algorithmic Fusion for More Robust Feature Tracking
International Journal of Computer Vision, 2002zbMATH Open Web Interface contents unavailable due to conflicting licenses.
McCane, Brendan +2 more
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Feature Fusion Using Complex Descriminator
2006This chapter describes feature fusion techniques using complex discriminator. After the introduction, we first introduce serial and parallel feature fusion strategies. Then, the complex linear projection analysis methods, complex PCA and complex LDA, are developed. Next, some feature preprocessing techniques are given. The symmetry property of parallel
David Zhang, Xiao-Yuan Jing, Jian Yang
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