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322 results on '"Gao, Yating"'

3. DREAM-PCD: Deep Reconstruction and Enhancement of mmWave Radar Pointcloud

Author

Geng, Ruixu, Li, Yadong, Zhang, Dongheng, Wu, Jincheng, Gao, Yating, Hu, Yang, and Chen, Yan

Subjects
Electrical Engineering and Systems Science - Image and Video Processing, Computer Science - Robotics
Abstract

Millimeter-wave (mmWave) radar pointcloud offers attractive potential for 3D sensing, thanks to its robustness in challenging conditions such as smoke and low illumination. However, existing methods failed to simultaneously address the three main challenges in mmWave radar pointcloud reconstruction: specular information lost, low angular resolution, and strong interference and noise. In this paper, we propose DREAM-PCD, a novel framework that combines signal processing and deep learning methods into three well-designed components to tackle all three challenges: Non-Coherent Accumulation for dense points, Synthetic Aperture Accumulation for improved angular resolution, and Real-Denoise Multiframe network for noise and interference removal. Moreover, the causal multiframe and "real-denoise" mechanisms in DREAM-PCD significantly enhance the generalization performance. We also introduce RadarEyes, the largest mmWave indoor dataset with over 1,000,000 frames, featuring a unique design incorporating two orthogonal single-chip radars, lidar, and camera, enriching dataset diversity and applications. Experimental results demonstrate that DREAM-PCD surpasses existing methods in reconstruction quality, and exhibits superior generalization and real-time capabilities, enabling high-quality real-time reconstruction of radar pointcloud under various parameters and scenarios. We believe that DREAM-PCD, along with the RadarEyes dataset, will significantly advance mmWave radar perception in future real-world applications., Comment: 13 pages, 9 figures

Published
2023

21. Distant Supervised Relation Extraction Based on Sentence-Level Attention with Relation Alignment

Author

Li, Jing, Huang, Xingjie, Gao, Yating, Liu, Jianyi, Zhang, Ru, Zhao, Jinmeng, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Sun, Xingming, editor, Zhang, Xiaorui, editor, and Xia, Zhihua, editor

Published
2022
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31. Carrier Robust Reversible Watermark Model Based on Image Block Chain Authentication

Author

Gao, Yating, Zhang, Ru, Li, Xianxu, Liu, Jianyi, Zhao, Kaifeng, Cheng, Xue, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Peng, Yuxin, editor, Hu, Shi-Min, editor, Gabbouj, Moncef, editor, Zhou, Kun, editor, Elad, Michael, editor, and Xu, Kun, editor

Published
2021
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34. Effects of Coal Mining Activities on the Changes in Microbial Community and Geochemical Characteristics in Different Functional Zones of a Deep Underground Coal Mine.

Author

Xu, Zhimin, Zhang, Li, Gao, Yating, Tan, Xianfeng, Sun, Yajun, and Chen, Weixiao

Subjects
MINES & mineral resources, MICROBIAL communities, WATER pollution prevention, MINE water, SULFATE-reducing bacteria, SOIL microbial ecology, MICROBIAL diversity, COAL mining, COALFIELDS
Abstract

For deep underground coal mining ecosystems, research on microbial communities and geochemical characteristics of sediments in different functional zones is lacking, resulting in the knowledge of zone-level mine water pollution prevention and control being narrow. In this study, we surveyed the geochemical distinctions and microbial communities of five typical functional zones in a representative North China coalfield, Xinjulong coal mine. The data indicated that the geochemical compounds and microbial communities of sediments showed distinguishing features in each zone. The microbial community richness and diversity were ranked as follows: surface water > rock roadways > sumps > coal roadways ≥ goafs. Canonical Correlation Analysis (CCA), Spearman correlation and co-occurrence network analysis demonstrated that microbial communities were sensitive and closely related to hydrochemical processes. The microbial community distribution in the underground mine was closely related not only to nutrient elements (i.e., C, S, P and N), but also to redox-sensitive substances (i.e., Fe and As). When it comes to mine water pollution prevention and control, the central zones are goafs. With the increase in goaf closure time, total nitrogen (TN), total organic carbon (TOC) and total sulfur (TS) decreased, but As, Fe and total phosphorus (TP) gradually increased, and the characteristic pollutant SO42− concentration in water samples decreased. Additionally, the sulfate-reducing bacteria (SRB) had relatively higher proportions in goafs, suggesting goafs were able to purify themselves. In practical engineering, in situ nitrogen injection technology used to expel oxygen and create an anaerobic environment can be implemented to enhance SRB reducing sulfate in goafs. Meanwhile, because coal mine pollution discharge generally only discharges mine water and leaves sediment underground, the pollutants can be transferred to the sediment by strengthening the relevant reactions including the heavy metal solidification and stabilization function of bacteria. [ABSTRACT FROM AUTHOR]

Published
2024
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