Zobrazeno 1 - 10 of 23 pro vyhledávání: '"Boqing Zhu"'
1
Akademický článek
Masked Modeling-Based Ultrasound Image Classification via Self-Supervised Learning
Autor: Kele Xu, Kang You, Boqing Zhu, Ming Feng, Dawei Feng, Cheng Yang
Publikováno v: IEEE Open Journal of Engineering in Medicine and Biology, Vol 5, Pp 226-237 (2024)
Recently, deep learning-based methods have emerged as the preferred approach for ultrasound data analysis. However, these methods often require large-scale annotated datasets for training deep models, which are not readily available in practical scen
Externí odkaz: https://doaj.org/article/6f9220eb1a9748cab67b3e7e517e7665
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2
Akademický článek
Self-Supervised Learning-For Underwater Acoustic Signal Classification With Mixup
Autor: Qisheng Xu, Jingfei Jiang, Kele Xu, Yong Dou, Caili Gao, Boqing Zhu, Kang You, Qian Zhu
Publikováno v: IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 17, Pp 3530-3542 (2024)
Underwater acoustic signal classification is a critical task that involves identifying different types of signals in a complex and dynamic underwater environment, which is often contaminated by strong ambient noise. Recent studies have demonstrated t
Externí odkaz: https://doaj.org/article/638864b7334749b99858dae0cbe1813f
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3
Akademický článek
Detection of Typical Transient Signals in Water by XGBoost Classifier Based on Shape Statistical Features: Application to the Call of Southern Right Whale
Autor: Zemin Zhou, Yanrui Qu, Boqing Zhu, Bingbing Zhang
Publikováno v: Journal of Marine Science and Engineering, Vol 12, Iss 9, p 1596 (2024)
Whale sound is a typical transient signal. The escalating demands of ecological research and marine conservation necessitate advanced technologies for the automatic detection and classification of underwater acoustic signals. Traditional energy detec
Externí odkaz: https://doaj.org/article/f0d3b30982024cfeaba3342e03b40df3
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4
Akademický článek
An Adversarial Feature Distillation Method for Audio Classification
Autor: Liang Gao, Haibo Mi, Boqing Zhu, Dawei Feng, Yicong Li, Yuxing Peng
Publikováno v: IEEE Access, Vol 7, Pp 105319-105330 (2019)
The audio classification task aims to discriminate between different audio signal types. In this task, deep neural networks have achieved better performance than the traditional shallow architecture-based machine-learning method. However, deep neural
Externí odkaz: https://doaj.org/article/74fc699c55d743cf944c1764b06ad26e
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9
Trust-worth multi-representation learning for audio classification with uncertainty estimation
Autor: Kele Xu, Kang You, Ming Feng, Boqing Zhu
Publikováno v: The Journal of the Acoustical Society of America. 153:A125-A125
Multi-view learning has been explored for audio classification tasks, exploiting different representations of audio signals, ranging from MFCC, CQT, to raw signals. The quality of each view may vary for different audio signals, and the appropriate un
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::7f0ef1a3a8f455e3b46cd5b40d06321a
https://doi.org/10.1121/10.0018383
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10
Rasterize the Lidar Point Cloud on The Ground Out Method Optimization Analysis
Autor: Chang Liu, Haiyun Gan, Jialin Li, Boqing Zhu
Publikováno v: Journal of Physics: Conference Series. 2405:012005
This paper is mainly aimed at the over-segmentation or under-segmentation phenomenon of the ground point cloud in the moving scene of the unmanned platform to identify the target. This paper proposes an optimized rasterization method to remove the gr
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::b2db9d31b0e260f5693ee4706ce7cfc1
https://doi.org/10.1088/1742-6596/2405/1/012005
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