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Published in 2020 at "Computer methods and programs in biomedicine"
DOI: 10.1016/j.cmpb.2019.105288
Abstract: BACKGROUND AND OBJECTIVE Automatic cardiac left ventricle (LV) quantification plays an important role in assessing cardiac function. Although many advanced methods have been put forward to quantify related LV parameters, automatic cardiac LV quantification is…
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Keywords:
deep multi;
quantification;
left ventricle;
multi task ... See more keywords
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Published in 2020 at "Procedia Manufacturing"
DOI: 10.1016/j.promfg.2020.10.164
Abstract: Abstract In advanced industries such as aerospace, medical and automotive, high precision machining is increasingly required for many parts made by difficult-to-cut alloys. Machine tool manufacturers respond to this demand by developing more advanced machine…
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Keywords:
big data;
energy;
multi layer;
deep multi ... See more keywords
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Published in 2018 at "IEEE Access"
DOI: 10.1109/access.2018.2851382
Abstract: Although the preclinical detection of Parkinson’s disease (PD) has been explored, a practical, inexpensive, and overall screening diagnosis has yet to be made available. However, due to the large variability and complexity in progress of…
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Keywords:
parkinson;
multi layer;
disease;
deep multi ... See more keywords
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Published in 2021 at "IEEE Communications Letters"
DOI: 10.1109/lcomm.2021.3063464
Abstract: This letter aims to reduce huge pilot overhead when estimating the reconfigurable intelligent surface (RIS) relayed wireless channel. Motivated by the compelling grasp of deep learning in tackling nonlinear mapping problems, the proposed approach only…
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Keywords:
reconfigurable intelligent;
deep multi;
stage;
intelligent surface ... See more keywords
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Published in 2022 at "IEEE/ACM Transactions on Computational Biology and Bioinformatics"
DOI: 10.1109/tcbb.2022.3150280
Abstract: The recognition of DNA- (DBPs) and RNA-binding proteins (RBPs) is not only conducive to understanding cell function, but also a challenging task. Previous studies have shown that these proteins are usually considered separately due to…
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Keywords:
joint learning;
binding proteins;
deep multi;
multi label ... See more keywords
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Published in 2021 at "IEEE Transactions on Intelligent Transportation Systems"
DOI: 10.1109/tits.2020.2972974
Abstract: Recent advancements in perception for autonomous driving are driven by deep learning. In order to achieve robust and accurate scene understanding, autonomous vehicles are usually equipped with different sensors (e.g. cameras, LiDARs, Radars), and multiple…
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Keywords:
multi modal;
detection semantic;
deep multi;
object detection ... See more keywords
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Published in 2021 at "Applied Sciences"
DOI: 10.3390/app11041884
Abstract: Dynamic spectrum access (DSA) has been considered as a promising technology to address spectrum scarcity and improve spectrum utilization. Normally, the channels are related to each other. Meanwhile, collisions will be inevitably caused by communicating…
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Keywords:
deep multi;
reinforcement learning;
spectrum;
user reinforcement ... See more keywords
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Published in 2022 at "Informatics"
DOI: 10.3390/informatics9040091
Abstract: Breast cancer accounts for 30% of all female cancers. Accurately distinguishing dangerous malignant tumors from benign harmless ones is key to ensuring patients receive lifesaving treatments on time. However, as doctors currently do not identify…
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Keywords:
classification;
breast cancer;
deep multi;
multi resolution ... See more keywords