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2019 IEEE International Conference on Signal, information and Data Processing, ICSIDP 2019

作者： Xie, Chaoyu Chen, Xuejin CAS Key Laboratory of Technology in Geo-spatial Information Processing and Application System University of Science and Technology of China Hefei China

ISBN: (纸本)9781728123455

Video stitching remains a challenging problem in computer vision. In this paper, we propose a novel edge-guided method to stitch multiple videos that have small overlapped regions. Our algorithm consists of three steps: (1) spherical projection of the input video frames based on camera calibration, (2) edge detection and edge-guided feature matching for video registration, and (3) seam optimization to eliminate distortions and ghosts in the composited panoramic videos. The experimental results and user studies demonstrate that our method is robust to videos that have small overlapped regions and produces more visually pleasing panoramic videos than state-of-the-art techniques. © 2019 IEEE.

关键词： Edge detection

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TEMPORAL and spatial VARIATION CHARACTERISTICS of PM2.5 CONCENTRATION in 2+26 CITIES

TEMPORAL and SPATIAL VARIATION CHARACTERISTICS of PM2.5 CONC...

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2020 International Conference on geomatics in the Big Data Era, ICGBD 2020

作者： Liang, L.S. Jing, J.L. Wang, A.N. Luo, F.L. College of Geomatics and Geo-information Guilin University of Technology China Guangxi Key Laboratory of Spatial Information and Geomatics Guilin541004 China

In recent years, air pollution is still a serious problem in China. Therefore, the government has further strengthened the pollution control measures for the Beijing-Tianjin-Hebei (BTH) air pollution transmission channel cities (2+26 cities). This study used real-time PM2.5 monitoring data from 176 air quality monitoring sites in 2+26 cities from 2015 to 2018. The temporal and spatial evolution characteristics of PM2.5 concentration in 2+26 cities were analysis by statistical analysis and Kriging interpolation method. The research results showed that: (1) From the analysed of time variation, the hourly variation presents a bimodal distribution, with the PM2.5 concentration reaching the peak at 9:00-10:00 O'clock and 22:00-00:00, and finally dropping to the lowest value at 16:00-17:00. The monthly change of PM2.5 concentration was almost the same, reaching the peak pollution concentration in December. The seasonal variation trend of the study area was almost the same, and the PM2.5 concentration had a small decline, except for the special changed in winter. However, autumn and winter were still the most polluted seasons, while the spring and summer were less polluted. (2) From the analysed of spatial variation, the pollution process started in November and ended slowly in March of the following year, with the worst and most extensive pollution in December. It was spread to surrounding cities by Baoding, Shijiazhuang, Xingtai and Handan in the central region, and the central area was the most polluted. In August, PM2.5 concentration was the lightest, with an average concentration of 42.4 μg/m3. © Authors 2020.

关键词： Statistical methods

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BURST-LDA: A NEW TOPIC MODEL FOR DETECTING BURSTY TOPICS FROM STREAM TEXT

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Journal of Electronics(China) 2014年第6期31卷 565-575页

作者： Qi Xiang Huang Yu Chen Ziyan Liu Xiaoyan Tian Jing Huang Tinglei Wang Hongqi Key Laboratory of Technology in Geo-spatial Information Processing and Application System Institute of Electronics Chinese Academy of Sciences University of Chinese Academy of Sciences

Topic models such as Latent Dirichlet Allocation(LDA) have been successfully applied to many text mining tasks for extracting topics embedded in corpora. However, existing topic models generally cannot discover bursty topics that experience a sudden increase during a period of time. In this paper, we propose a new topic model named Burst-LDA, which simultaneously discovers topics and reveals their burstiness through explicitly modeling each topic's burst states with a first order Markov chain and using the chain to generate the topic proportion of documents in a Logistic Normal fashion. A Gibbs sampling algorithm is developed for the posterior inference of the proposed model. Experimental results on a news data set show our model can efficiently discover bursty topics, outperforming the state-of-the-art method.

关键词： Text mining Burst detection Topic model Graphical model Bayesian inference

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A novel synthetic aperture radar scattering model for sea surface with breaking waves

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Acta Oceanologica Sinica 2022年第4期41卷 138-145页

作者： Xiaochen Wang Yuxin Hu Bing Han Wei Tian Chunhua Zhang Aerospace Information Research Institute Chinese Academy of SciencesBeijing 100094China Key Laboratory of Technology in Geo-spatial Information Processing and Application System Chinese Academy of SciencesBeijing 100190China The box51111 Beijing 100190China

In this study a novel synthetic aperture radar(SAR)scattering model for sea surface with breaking waves is *** with existing models,the proposed model considers an empirical relationship between wind speed and wave breaking scattering to present the contribution of wave ***,the scattering weight factor p,and wave breaking rate q,are performed to present the contribution of the quasi-specular scattering term,Bragg scattering term,and wave breaking scattering term to the total scattering from the sea *** explore the modeling accuracy of sea-surface scattering,a simulated normalized radar cross-section(NRCS)and measured NRCS are *** proposed model generated the simulated NRCS and a matching GF-3 dataset was used for the measured *** was revealed that the performance of the VV polarization of our model was much better than that of HH polarization,with a correlation of 0.91,bias of-0.14 dB,root mean square error(RMSE)of 1.26 dB,and scattering index(SI)*** addition,the novel model is explored and compared with the geophysical model of CMODs and satellite-measured NRCS from GF-3 SAR wave mode *** an incidence angle 40°–41°,the relationship between the NRCS and wind speed,relative wind direction is *** with the SAR-measured NRCS,the performance of VV polarization was much better than HH polarization,with a correlation of 0.99,bias of-0.25 dB,RMSE of 0.64 dB,and SI of-0.04.

关键词： synthetic aperture radar scattering model sea surface wave breaking

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NON-PARAMETRIC TOPIC MODEL FOR DISCOVERING geoGRAPHICAL TOPIC VARIATIONS

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Journal of Electronics(China) 2014年第6期31卷 576-586页

作者： Qi Xiang Huang Yu Song Jun Huang Tinglei Wang Hongqi Fu Kun Key Laboratory of Technology in Geo-spatial Information Processing and Application System Institute of Electronics Chinese Academy of Sciences University of Chinese Academy of Sciences

This paper presents a non-parametric topic model that captures not only the latent topics in text collections, but also how the topics change over space. Unlike other recent work that relies on either Gaussian assumptions or discretization of locations, here topics are associated with a distance dependent Chinese Restaurant Process(ddC RP), and for each document, the observed words are influenced by the document's GPS-tag. Our model allows both unbound number and flexible distribution of the geographical variations of the topics' content. We develop a Gibbs sampler for the proposal, and compare it with existing models on a real data set basis.

关键词： Text mining Topic model geographical topics Bayesian non-parameter

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Effect of Microgroove Structure on the Performance of QTFs Utilized for Gas Sensing

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IEEE Transactions on Instrumentation and Measurement 2025年 74卷

作者： Yi Wang Shaoning Zheng Dongfang Shao Feihu Fang Yilü Tao Shengshou Lin Renpeng Yan Yufei Ma Jinxing Liang Key Laboratory of Micro-Inertial Instrument and Advanced Navigation Technology Ministry of Education School of Instrument Science and Engineering Southeast University Nanjing China National Key Laboratory of Laser Spatial Information Harbin Institute of Technology Harbin China

The quartz tuning fork (QTF), serving as the acoustic-electrical conversion element in quartz enhanced photoacoustic spectroscopy (QEPAS) systems, plays a critical role in determining detection sensitivity. In this study, we establish, for the first time, a comprehensive model of the acoustic-mechanical–electrical transformations in QTFs for gas sensing applications, leveraging this model to optimize their structural design. By enhancing key intrinsic properties of QTFs—such as resonance frequency, quality factor (Q), and surface excitation charge—the optimized design significantly improves the efficiency and sensitivity of gas measurements. Specifically, the influence of microgroove depth and width on the performance of T-shaped QTFs is systematically investigated through theoretical analysis and numerical simulations. Guided by the optimization framework, two sets of QTFs were fabricated: one featuring grooves of varying depths and the other with grooves of varying widths. These QTFs were subsequently employed in trace gas detection experiments to validate the theoretical predictions. The experimental results demonstrate that the T-shaped microgroove QTFs achieve substantial performance enhancements, with signal peak and signal-to-noise ratio (SNR) improvements of up to 234% and 577%, respectively, compared to standard 32.768 kHz commercial QTFs, as evidenced by C2H2 measurements.

关键词： Resonance Q-factor Vibrations Force Spectroscopy Resonant frequency Sensitivity Resistance Standards Signal to noise ratio

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Nonparametric statistics inspired similarity measure for accuracy in collaborative filtering

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Journal of Computational information Systems 2013年第20期9卷 8397-8406页

作者： Liu, Shichen Xiong, Yan Liu, Qingwen Qi, Xiang Department of Computer Science and Technology University of Science and Technology of China Hefei 230027 China Key Laboratory of Technology in Geo-Spatial Information Processing and Application System Institute of Electronics Chinese Academy of Sciences Beijing 100190 China

Similarity computation is especially significant in collaborative filtering algorithms. In the existed literatures or large recommender systems, researchers generally use cosine similarity or Pearson correlation coefficient to compute the similarities. However, on one hand, both two measures are more applicable in linear space while the ratings cannot linearly reflect users' interest intensity. On the other hand, different systems have different rating restricts, so it's unreasonable to treat varied systems with the same computation method. In this work, inspired by nonparametric statistics, a sound memory-based method with a novel similarity measure is proposed to eliminate the affection of rating distributions and system diversities on similarity computation. Experiments based on Jester are set to evaluate the performance of the approach. And the highly competitive results show that our approach is able to significantly improve the recommendation quality. © 2013 Binary information Press.

关键词： Collaborative filtering

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A joint high-resolution processing method and its application for thin inter-beds

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Petroleum Science 2013年第2期10卷 195-204页

作者： Liu Zhiwei Wang Yanchun School of Geophysics and Information Technology China University of Geosciences Key Laboratory of Geo-detection Ministry of EducationChina University of Geosciences

Seismic processing characterizing thickness and borders of thin inter-beds has gradually evolved fi＇om post-stack migration to pre-stack migration, and the latter considers both vertical and lateral resolutions. As the key processing methods for improving vertical and lateral resolution, conventional deconvolution and pre-stack time migration （PSTM） are not simply dominated by the estimation and compression of the wavelet because of its instability. Therefbre, considering the variations of wavelet frequency belbre, during and alter PSTM can obtain good common reflection point （CRP） gathers and imaging profiles of thin inter-beds. Based on the frequency characteristics of the wavelet before, during and after PSTM, a joint high-resolution processing method for thin inter-beds is proposed in this paper, including inverse Q filtering for high-frequency compensation before PSTM, optimum weighting Kirchhoff PSTM for preserving high-frequencies during PSTM, and wavelet harmonizer deconvolution tier consistent processing and frequency-band broadening after PSTM. An application to real data characterized by mudstone beds in the Oriente Basin proved that the joint high-resolution processing method is effective for determining the thickness and borders of thin inter-beds and is favorable for subsequent reservoir prediction and seismic inversions.

关键词： Thin inter-bed seismic wavelet inverse Q filtering optimum weight function harmonizerdeconvolution

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CNN-BASED DEPTH MAP PREDICTION FOR FAST BLOCK PARTITIONING IN HEVC INTRA CODING

CNN-BASED DEPTH MAP PREDICTION FOR FAST BLOCK PARTITIONING I...

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2021 IEEE International Conference on Multimedia and Expo, ICME 2021

作者： Feng, Aolin Gao, Changsheng Li, Li Liu, Dong Wu, Feng CAS Key Laboratory of Technology in Geo-Spatial Information Processing and Application System University of Science and Technology of China Hefei230027 China

ISBN: (纸本)9781665438643

High Efficiency Video Coding (HEVC) achieves significant improvement in compression efficiency by introducing quadtree-based block partition. However, in the HEVC reference software-HM, the optimal partition is found by a recursive rate-distortion optimization (RDO) process, which is computationally expensive and not friendly to hardware implementation. We propose a fast block partitioning algorithm using convolutional neural network (CNN) based depth map prediction for HEVC intra coding. We use the depth map to represent the block partition of a coding tree unit (CTU). Then, we design a CNN to predict the depth map for a CTU, and we construct a large-scale dataset to train the CNN. Through the depth map prediction, we obtain a block partitioning structure for the entire CTU, and then we could directly compress each coding unit, getting rid of the recursive RDO process for partitioning. Experimental results show that our proposed method reduces 65.55% encoding time of HM at the cost of 2.02% Bjøntegaard Delta rate (BD-rate) increase on the common test sequences. For 4K sequences, our method achieves 76.97% time saving with 2.89% BD-rate increase. © 2021 IEEE

关键词： Forecasting

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Learning Disentangled Feature Representation for Hybrid-Distorted Image Restoration 1

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16th European Conference on Computer Vision, ECCV 2020

作者： Li, Xin Jin, Xin Lin, Jianxin Liu, Sen Wu, Yaojun Yu, Tao Zhou, Wei Chen, Zhibo CAS Key Laboratory of Technology in Geo-Spatial Information Processing and Application System University of Science and Technology of China Hefei230027 China

ISBN: (数字)9783030585266

ISBN: (纸本)9783030585259

Hybrid-distorted image restoration (HD-IR) is dedicated to restore real distorted image that is degraded by multiple distortions. Existing HD-IR approaches usually ignore the inherent interference among hybrid distortions which compromises the restoration performance. To decompose such interference, we introduce the concept of Disentangled Feature Learning to achieve the feature-level divide-and-conquer of hybrid distortions. Specifically, we propose the feature disentanglement module (FDM) to distribute feature representations of different distortions into different channels by revising gain-control-based normalization. We also propose a feature aggregation module (FAM) with channel-wise attention to adaptively filter out the distortion representations and aggregate useful content information from different channels for the construction of raw image. The effectiveness of the proposed scheme is verified by visualizing the correlation matrix of features and channel responses of different distortions. Extensive experimental results also prove superior performance of our approach compared with the latest HD-IR schemes. © 2020, Springer Nature Switzerland AG.

关键词： Image reconstruction

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