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Published in 2020 at "Geocarto International"
DOI: 10.1080/10106049.2020.1753819
Abstract: In order to improve the cross-domain applicability of road segmentation, a feature transfer based adversarial domain adaptation method is presented for cross-domain road extraction. The presented m...
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Keywords:
cross domain;
road;
domain;
feature transfer ... See more keywords
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Published in 2020 at "IEEE Access"
DOI: 10.1109/access.2020.2992520
Abstract: Detecting the frequency of the pest occurrence is always a time consuming and laborious task for agriculture. This paper attempts to solve the problem through the combination of deep learning and pest detection. We propose…
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Keywords:
feature transfer;
feature;
detecting frequency;
transfer learning ... See more keywords
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Published in 2023 at "IEEE Access"
DOI: 10.1109/access.2023.3240306
Abstract: In order to build an effective condition monitoring (CM) model for the target wind turbines (WTs) with few operational data, an approach based on the feature transfer learning and a modified generative adversarial network is…
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Keywords:
condition monitoring;
feature transfer;
transfer;
transfer learning ... See more keywords
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Published in 2021 at "IEEE Transactions on Circuits and Systems II: Express Briefs"
DOI: 10.1109/tcsii.2021.3060896
Abstract: Deep neural networks are susceptible to poisoning attacks by purposely polluted training data with specific triggers. As existing episodes mainly focused on attack success rate with patch-based samples, defense algorithms can easily detect these poisoning…
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Keywords:
deeppoison;
transfer based;
feature transfer;
deeppoison feature ... See more keywords
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Published in 2023 at "IEEE Transactions on Instrumentation and Measurement"
DOI: 10.1109/tim.2023.3269105
Abstract: Noninvasive load monitoring (NILM) aims to extract the power consumption of individual appliances from a smart meter that measures the total power consumption of all appliances. At present, deep learning methods have achieved leading results.…
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Keywords:
feature transfer;
transfer;
transfer learning;
adaptive fusion ... See more keywords
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Published in 2024 at "Applied Engineering in Agriculture"
DOI: 10.13031/aea.16080
Abstract: HighlightsPowdery mildew diagnostic system has been established for identifying diseased leaves in the complex backgrounds.The degree of disease has been quantified to improve the computational efficiency of the recognition model.A diagnostic system for early powdery…
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Keywords:
powdery mildew;
disease;
feature transfer;
mildew ... See more keywords