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Published in 2019 at "Wireless Networks"
DOI: 10.1007/s11276-017-1655-2
Abstract: In recent years, several correlation tracking algorithms have been proposed exploiting hierarchical features from deep convolutional neural networks. However, most of these methods focus on utilizing the hierarchical features for target translation and use a…
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Keywords:
scale adaptive;
based convolutional;
tracking based;
adaptive correlation ... See more keywords
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Published in 2021 at "IEEE Access"
DOI: 10.1109/access.2021.3111532
Abstract: Discriminative correlation filters (DCF) have drawn increasing interest in visual tracking. In particular, a few recent works treat DCF as a special layer and add it into a Siamese network for visual tracking. However, most…
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Keywords:
end end;
end;
level;
feature fusion ... See more keywords
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Published in 2021 at "IEEE Transactions on Image Processing"
DOI: 10.1109/tip.2020.3037518
Abstract: The training of a feature extraction network typically requires abundant manually annotated training samples, making this a time-consuming and costly process. Accordingly, we propose an effective self-supervised learning-based tracker in a deep correlation framework (named:…
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Keywords:
self supervised;
feature extraction;
extraction network;
correlation ... See more keywords
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Published in 2018 at "Journal of Astronomical Telescopes, Instruments, and Systems"
DOI: 10.1117/1.jatis.4.1.018001
Abstract: Abstract. The Multi-Order Solar EUV Spectrograph (MOSES) is a sounding rocket instrument that utilizes a concave spherical diffraction grating to form simultaneous images in the diffraction orders m=0, +1, and −1. MOSES is designed to…
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Keywords:
information;
spectrograph;
correlation tracking;
doppler shift ... See more keywords