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Your search keyword '"Liu, Yundong"' showing total 34 results
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34 results on '"Liu, Yundong"'

9. Adaptive adjacent context negotiation network for object detection in remote sensing imagery.

Author

Dong, Yan, Liu, Yundong, Cheng, Yuhua, Gao, Guangshuai, Chen, Kai, and Li, Chunlei

Subjects
DISASTER relief, EMERGENCY management, SPECTRAL imaging, NEGOTIATION, RESOURCE management
Abstract

Accurate localization of objects of interest in remote sensing images (RSIs) is of great significance for object identification, resource management, decision-making and disaster relief response. However, many difficulties, like complex backgrounds, dense target quantities, large-scale variations, and small-scale objects, which make the detection accuracy unsatisfactory. To improve the detection accuracy, we propose an Adaptive Adjacent Context Negotiation Network (A2CN-Net). Firstly, the composite fast Fourier convolution (CFFC) module is given to reduce the information loss of small objects, which is inserted into the backbone network to obtain spectral global context information. Then, the Global Context Information Enhancement (GCIE) module is given to capture and aggregate global spatial features, which is beneficial for locating objects of different scales. Furthermore, to alleviate the aliasing effect caused by the fusion of adjacent feature layers, a novel Adaptive Adjacent Context Negotiation network (A2CN) is given to adaptive integration of multi-level features, which consists of local and adjacent branches, with the local branch adaptively highlighting feature information and the adjacent branch introducing global information at the adjacent level to enhance feature representation. In the meantime, considering the variability in the focus of feature layers in different dimensions, learnable weights are applied to the local and adjacent branches for adaptive feature fusion. Finally, extensive experiments are performed in several available public datasets, including DIOR and DOTA-v1.0. Experimental studies show that A2CN-Net can significantly boost detection performance, with mAP increasing to 74.2% and 79.2%, respectively. [ABSTRACT FROM AUTHOR]

Published
2024
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31. High sensitivity plasmonic temperature sensor based on a side-polished photonic crystal fiber.

Author

Gao, Zhigang, 高, 治刚, Jing, Xili, äş•, 西利, Liu, Yundong, 刘, äş'东, Chen, Hailiang, 陈, 海良, Li, Shuguang, and 李, ć›™ĺ...‰

Subjects
PHOTONIC crystal fibers, TEMPERATURE sensors, SURFACE plasmon resonance, PLASMONICS, FINITE element method, TEMPERATURE measurements
Abstract

A high sensitivity plasmonic temperature sensor based on a side-polished photonic crystal fiber is proposed in this work. In order to achieve high sensitivity and high stability, the gold layer is coated on the side-polished photonic crystal fiber to support surface plasmon resonance. The mixture of ethanol and chloroform is used as the thermosensitive liquid. The performances of the proposed temperature sensor were investigated by the finite element method (FEM). Simulation results indicate that the sensitivity of the temperature sensor is as high as 7.82 nm/°C. It has good linearity (R 2 = 0.99803), the resolution of 1.1 Ă— 10âˆ'3 °C, and the amplitude sensitivity of 0.1008 °Câˆ'1. In addition, the sizes of the small air hole and polishing depth have little influence on the sensitivity. Therefore, the proposed sensor shows a high structure tolerance. The excellent performance and high structure tolerance of the sensor make it an appropriate choice for temperature measurement. [ABSTRACT FROM AUTHOR]

Published
2022
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33. High-performance surface plasmon resonance refractometer based on a no-core fiber coated with a silver film

Author

Liu, Yundong, Chen, Hailiang, Li, Hongyu, Zhang, Song, Gao, Zhigang, Feng, Yuhui, Zhang, Yingyue, and Li, Shuguang

Abstract

Owing to their high sensitivity, surface plasmon resonance (SPR)-based sensors depict broad application prospects in biochemical detection, environmental monitoring, and food safety. In this paper, an optical fiber-based SPR sensor is proposed and demonstrated for the refractive index (RI) detection of liquid samples. This sensor is composed of a multimode fiber (MMF), a no-core fiber (NCF), and another MMF that is connected in sequence. The length of the NCF is 2 cm. A thin silver film is deposited on the NCF surface to stimulate the SPR effect. Experimental results indicated that the shift amount of resonance dip wavelength is as high as 303.6 nm as RI increases from 1.333 to 1.4107. A sensitivity of 2507.58 nm/RIU with a fitting linearity R^2 of 0.9931 is obtained in the lower RI region of 1.333–1.3723, while the sensitivity and R^2 reaches 5228.21 nm/RIU and 0.97395, respectively, in the higher RI region of 1.3723–1.4107. Compared with previously reported RI sensors, the proposed fiber optic SPR sensor exhibits the advantages of simple structure, small volume, low cost, high sensitivity, and wide detection range.

Published
2021

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