作者: Xie, C.;Wu, Q.;Wu, H.;Liu, G. (School of Information and Electronics, Beijing Institute of Technology, Beijing, China)
出处: Advances in Intelligent Systems and Computing 2019 Vol.752 P1255-1262
关键词: Empirical Mode Decomposition (EMD);Vibration signal process;Water-injection pump
摘要: According to the working condition and the common fault causes of the water-injection pump, this paper introduces a data acquisition and signal proces ...
作者: ZHANG Lujie1;GUO Dechun1; (School of Information and Electronics, Beijing Institute of Technology, 5 Hainan, Beijing, China)
出处: IOP Conference Series: Materials Science and Engineering 2019 Vol.563 No.5 P052024
摘要: This paper proposes a double threshold detection algorithm based on mutual trust degree correction, in order to reduce the probability of missed detec ...
作者: Weijiang Wang;Runyi Wang;Rongkun Jiang;Hao Yang;Xiaoyu Wang (School of Information and Electronics, Beijing Institute of Technology School of Information and Electronics, Beijing Institute of Technology School of Information and Electronics, Beijing Institute of Technology School of Information and Electronics, Beijing Institute of Technology School of Information and Electronics, Beijing Institute of Technology)
出处: The Journal of Engineering 2019 Vol.2019 No.21 P7924-7927
关键词: doppler radar;radar clutter;radar detection;matrix algebra;probability;object detection;radar signal processing;modified reference window;two-dimensional cfar;radar target detection;constant false alarm rate technology;cell averaging cfar detectors;average interference power;range–doppler matrix;detection threshold;tolerably small rate;conventional rectangular window;cross window;column window;degraded detection performance;extraneous reference cells;radar targets;detection probability;cfar loss
摘要: The constant false alarm rate (CFAR) technology plays an important role in radar target detection. In cell averaging CFAR detectors, a reference windo ...
作者: Zhang Zengshuo;Tang Linbo;Han Yuqi;Nan Jinghong;Zhao Baojun (School of Information and Electronic, Beijing Institute of Technology School of Information and Electronic, Beijing Institute of Technology School of Information and Electronic, Beijing Institute of Technology School of Information and Electronic, Beijing Institute of Technology School of Information and Electronic, Beijing Institute of Technology)
出处: The Journal of Engineering 2019 Vol.2019 No.20 P6573-6576
关键词: image sequences;object detection;object tracking;image matching;long-term tracker;performance degradation;long-term tracking applications;fast scale estimation;scale variation;re-detection module;keypoint-matching based confidence indicator;fast translation calculation;correlation filter-based tracker;distance metric method;real-time speed;efficient re-detection scheme
摘要: In long-term tracking applications, occlusion and scale variation are common attributes which cause performance degradation. Existing solutions use he ...
作者: Li Zhen;Zhao Baojun;Tang Linbo;Wang Wenzheng;Zhao Boya (School of Information and Electronic, Beijing Institute of Technology School of Information and Electronic, Beijing Institute of Technology School of Information and Electronic, Beijing Institute of Technology School of Information and Electronic, Beijing Institute of Technology School of Information and Electronic, Beijing Institute of Technology)
出处: The Journal of Engineering 2019 Vol.2019 No.21 P7640-7643
关键词: natural scenes;image segmentation;geophysical image processing;remote sensing;image classification;clouds;atmospheric techniques;cloud detection algorithms;rs image;segment ragged cloud;cloud region;remote sensing image processing;qtsu method;natural scene statistic
摘要: Cloud detection plays a significant role in remote sensing (RS) image processing. Numbers of cloud detection algorithms have been developed in the lit ...
作者: Jiong Cai;Quan Yuan;Rui Wang;Changjiang Liu;Tianran Zhang (School of Information and Electronics, Beijing Institute of Technology School of Information and Electronics, Beijing Institute of Technology School of Information and Electronics, Beijing Institute of Technology School of Information and Electronics, Beijing Institute of Technology School of Information and Electronics, Beijing Institute of Technology)
出处: The Journal of Engineering 2019 Vol.2019 No.21 P7636-7639
关键词: radar cross-sections;radar signal processing;signal sampling;nearest neighbour methods;insect detection;radar-effective sampling volumes;rcs;radar cross-sections;nearest neighbour method;insect echo data;two-dimensional scanning mode;ku-band experimental entomological radar;insect density estimation;total insect density;height layer
摘要: Entomological radars need to address the problem of insect density estimation. Here, a Ku-band experimental entomological radar with two-dimensional s ...
作者: Fan Feng;Baojun Zhao;Linbo Tang;Wenzheng Wang;Sen Jia (School of Information and Electronic, Beijing Institute of Technology School of Information and Electronic, Beijing Institute of Technology School of Information and Electronic, Beijing Institute of Technology School of Information and Electronic, Beijing Institute of Technology School of Information and Electronic, Beijing Institute of Technology)
出处: The Journal of Engineering 2019 Vol.2019 No.21 P7406-7409
关键词: geophysical image processing;hyperspectral imaging;geophysical techniques;hsi;hu;end-member extraction;abundance estimation methods;noise corruption;high-noise bands;estimation accuracy reduction;abundance estimation model;signal-to-noise ratio bands;synthetic data;real hyperspectral data;low-rank abundance matrix estimation;hyperspectral unmixing;hyperspectral image processing;water absorption;atmospheric transmission
摘要: Hyperspecral unmixing (HU) is one of the crucial steps of hyperspectral image (HSI) processing. The process of HU can be divided into end-member extra ...
作者: Li Zhenzhen;Zhao Baojun;Tang Linbo;Li Zhen;Feng Fan (School of Information and Electronic, Beijing Institute of Technology School of Information and Electronic, Beijing Institute of Technology School of Information and Electronic, Beijing Institute of Technology School of Information and Electronic, Beijing Institute of Technology School of Information and Electronic, Beijing Institute of Technology)
出处: The Journal of Engineering 2019 Vol.2019 No.21 P7343-7346
关键词: learning (artificial intelligence);ships;image classification;feature extraction;convolutional neural nets;limited labelled images;different imaging conditions;optical images;convolutional neural networks;optical ship images;achieving good classification performance;supervised learning;ship classification approach;complex images;handcrafted features;traditional methods focus
摘要: Ship classification in optical images has been challenged by the complexity of various ships, different imaging conditions, and limited labelled image ...
作者: Yang Li;Miaomiao Cheng;Xiangjun Peng;Bangsheng Zhuo;Feng Li (School of Information and Electronics, Beijing Institute of Technology School of Information and Electronics, Beijing Institute of Technology School of Information and Electronics, Beijing Institute of Technology School of Information and Electronics, Beijing Institute of Technology School of Information and Electronics, Beijing Institute of Technology)
出处: The Journal of Engineering 2019 Vol.2019 No.19 P6252-6254
关键词: radar imaging;object detection;ships;feature extraction;synthetic aperture radar;SAR image;one-dimensional target detection;range profiles;suspected targets;target region;target recognition;SAR ship data;one-dimensional range profile;image processing;synthetic aperture radar image
摘要: Target detection and recognition are two important parts in image processing. As it is known to authors, target detection in synthetic aperture radar ...
作者: Wang Wenzheng;Zhao Baojun;Tang Linbo;Zhou Shichao;Feng Fan (School of Information and Electronic, Beijing Institute of Technology School of Information and Electronic, Beijing Institute of Technology School of Information and Electronic, Beijing Institute of Technology School of Information and Electronic, Beijing Institute of Technology School of Information and Electronic, Beijing Institute of Technology)
出处: The Journal of Engineering 2019 Vol.2019 No.20 P6741-6744
关键词: image matching;image fusion;object detection;geophysical image processing;hyperspectral imaging;feature extraction;remote sensing;image classification;spectral analysis;hyperspectral target detection;fusion-based spectral matching method;spectral-matching methods;fusion-based method;target spectra samples;euclidean-angle matching method;hyperspectral target-detection task;fusion-based spectral-matching method;spectral gradient angle;spectral similarity metric methods;hyperspectral images
摘要: Target detection using hyperspectral images is one of the most important applications in the field of both civilian and military. Some spectral simila ...