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127 results on '"Liu, Yanxing"'

1. Locate Anything on Earth: Advancing Open-Vocabulary Object Detection for Remote Sensing Community

Author

Pan, Jiancheng, Liu, Yanxing, Fu, Yuqian, Ma, Muyuan, Li, Jiaohao, Paudel, Danda Pani, Van Gool, Luc, and Huang, Xiaomeng

Subjects
Computer Science - Computer Vision and Pattern Recognition
Abstract

Object detection, particularly open-vocabulary object detection, plays a crucial role in Earth sciences, such as environmental monitoring, natural disaster assessment, and land-use planning. However, existing open-vocabulary detectors, primarily trained on natural-world images, struggle to generalize to remote sensing images due to a significant data domain gap. Thus, this paper aims to advance the development of open-vocabulary object detection in remote sensing community. To achieve this, we first reformulate the task as Locate Anything on Earth (LAE) with the goal of detecting any novel concepts on Earth. We then developed the LAE-Label Engine which collects, auto-annotates, and unifies up to 10 remote sensing datasets creating the LAE-1M - the first large-scale remote sensing object detection dataset with broad category coverage. Using the LAE-1M, we further propose and train the novel LAE-DINO Model, the first open-vocabulary foundation object detector for the LAE task, featuring Dynamic Vocabulary Construction (DVC) and Visual-Guided Text Prompt Learning (VisGT) modules. DVC dynamically constructs vocabulary for each training batch, while VisGT maps visual features to semantic space, enhancing text features. We comprehensively conduct experiments on established remote sensing benchmark DIOR, DOTAv2.0, as well as our newly introduced 80-class LAE-80C benchmark. Results demonstrate the advantages of the LAE-1M dataset and the effectiveness of the LAE-DINO method., Comment: 10 pages, 5 figures

Published
2024

2. Impact of Transnational Second-Home Mobility on Tourism Experience and Quality of Life

Author

Liang Zengxian, Luo Hui, and Liu Yanxing

Subjects
transnational second home, push-pull theory, tourism experience, residential experience, life satisfaction, motivation, malaysia, Geography (General), G1-922
Abstract

Chinese people have become important international buyers of second homes in many destination countries, particularly Malaysia, Thailand, and other Southeast Asian countries. In the past decade, the aging population and the quest for a better life have become pressing concerns in China and have triggered an increase in transnational second-home purchases in other countries. However, despite the significant and rapid growth of transnational second homes in China, little is known about the nuanced relationship between buying motives and life satisfaction. Current studies in the Western context offer limited theoretical and practical implications for Chinese transnational second homes because Chinese buyers exhibit different motives and have a distinct understanding of a good life. Based on the push-pull theory, this study examines Chinese transnational second-home buyers' motivation and life satisfaction and the relationship between these two constructs. Data were drawn from 340 Chinese transnational second-home buyers of R&F Princess Cove in Johor Bahru, Malaysia. Structural equation modeling (SEM), Importance-Performance Map Analysis (IPMA), and multi-cluster analysis (MGA) were used to process the data. Our empirical results show that, in comparison to Western second-home buyers, Chinese second-home buyers' tourism and residential experiences and overall life satisfaction are significantly affected by pull motivations, while push motivations exhibit less influence. Among all the dimensions of push motivations, the natural and tourism environment, cultural and life atmosphere, and service facilities are crucial motivations in order of priority. Economic factors (such as prices and cost of living) also influence but are not the most important factors. Both tourism and residential experience significantly affect Chinese second-home buyers' overall life satisfaction, with residential experience exhibiting a higher influence. Women and larger second-home groups value residential experiences more than other groups, while smaller buyers value travel experiences more. This study provides new evidence for future studies on Chinese transnational second homes and responds to the current academic discussions on second-home buyers' motives in transnational contexts. Finally, this study has practical implications for domestic second-home destination construction and marketing.

Published
2024
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10. Ultrasound Image Preprocessing Method for Deep-Learning-Based Fatty Liver Diagnosis

Author

Hu, Yongle, Lian, Yusheng, Liu, Yanxing, Jin, Yang, Hu, Xiaojie, Liu, Zilong, Lin, Zixin, Li, Lingbo, He, Guannan, Chu, Yiyang, Angrisani, Leopoldo, Series Editor, Arteaga, Marco, Series Editor, Panigrahi, Bijaya Ketan, Series Editor, Chakraborty, Samarjit, Series Editor, Chen, Jiming, Series Editor, Chen, Shanben, Series Editor, Chen, Tan Kay, Series Editor, Dillmann, Rüdiger, Series Editor, Duan, Haibin, Series Editor, Ferrari, Gianluigi, Series Editor, Ferre, Manuel, Series Editor, Hirche, Sandra, Series Editor, Jabbari, Faryar, Series Editor, Jia, Limin, Series Editor, Kacprzyk, Janusz, Series Editor, Khamis, Alaa, Series Editor, Kroeger, Torsten, Series Editor, Liang, Qilian, Series Editor, Martín, Ferran, Series Editor, Ming, Tan Cher, Series Editor, Minker, Wolfgang, Series Editor, Misra, Pradeep, Series Editor, Möller, Sebastian, Series Editor, Mukhopadhyay, Subhas, Series Editor, Ning, Cun-Zheng, Series Editor, Nishida, Toyoaki, Series Editor, Pascucci, Federica, Series Editor, Qin, Yong, Series Editor, Seng, Gan Woon, Series Editor, Speidel, Joachim, Series Editor, Veiga, Germano, Series Editor, Wu, Haitao, Series Editor, Zhang, Junjie James, Series Editor, Zhao, Pengfei, editor, Ye, Zhuangzhi, editor, Xu, Min, editor, Yang, Li, editor, Zhang, Linghao, editor, and Zhu, Rengao, editor

Published
2021
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11. A privacy-preserving vehicle trajectory clustering framework.

Author

Tian, Ran, Gao, Pulun, and Liu, Yanxing

Abstract

Copyright of Frontiers of Information Technology & Electronic Engineering is the property of Springer Nature and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Published
2024
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13. Research on a Slice-Based Voxelization Method

Author

Liu, Yanxing, Lian, Yusheng, Jin, Yang, Hu, Xiaojie, Hu, Yongle, He, Guannan, Angrisani, Leopoldo, Series Editor, Arteaga, Marco, Series Editor, Panigrahi, Bijaya Ketan, Series Editor, Chakraborty, Samarjit, Series Editor, Chen, Jiming, Series Editor, Chen, Shanben, Series Editor, Chen, Tan Kay, Series Editor, Dillmann, Rüdiger, Series Editor, Duan, Haibin, Series Editor, Ferrari, Gianluigi, Series Editor, Ferre, Manuel, Series Editor, Hirche, Sandra, Series Editor, Jabbari, Faryar, Series Editor, Jia, Limin, Series Editor, Kacprzyk, Janusz, Series Editor, Khamis, Alaa, Series Editor, Kroeger, Torsten, Series Editor, Liang, Qilian, Series Editor, Martín, Ferran, Series Editor, Ming, Tan Cher, Series Editor, Minker, Wolfgang, Series Editor, Misra, Pradeep, Series Editor, Möller, Sebastian, Series Editor, Mukhopadhyay, Subhas, Series Editor, Ning, Cun-Zheng, Series Editor, Nishida, Toyoaki, Series Editor, Pascucci, Federica, Series Editor, Qin, Yong, Series Editor, Seng, Gan Woon, Series Editor, Speidel, Joachim, Series Editor, Veiga, Germano, Series Editor, Wu, Haitao, Series Editor, Zhang, Junjie James, Series Editor, Zhao, Pengfei, editor, Ye, Zhuangzhi, editor, Xu, Min, editor, and Yang, Li, editor

Published
2020
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14. Improved Spectral Reflectance Reconstruction Algorithm Based on Matrix R Method

Author

Hu, Xiaojie, Lian, Yusheng, Jin, Yang, Lin, Zixin, Liu, Yanxing, Huang, Min, Wang, Meng, He, Guannan, Angrisani, Leopoldo, Series Editor, Arteaga, Marco, Series Editor, Panigrahi, Bijaya Ketan, Series Editor, Chakraborty, Samarjit, Series Editor, Chen, Jiming, Series Editor, Chen, Shanben, Series Editor, Chen, Tan Kay, Series Editor, Dillmann, Rüdiger, Series Editor, Duan, Haibin, Series Editor, Ferrari, Gianluigi, Series Editor, Ferre, Manuel, Series Editor, Hirche, Sandra, Series Editor, Jabbari, Faryar, Series Editor, Jia, Limin, Series Editor, Kacprzyk, Janusz, Series Editor, Khamis, Alaa, Series Editor, Kroeger, Torsten, Series Editor, Liang, Qilian, Series Editor, Martín, Ferran, Series Editor, Ming, Tan Cher, Series Editor, Minker, Wolfgang, Series Editor, Misra, Pradeep, Series Editor, Möller, Sebastian, Series Editor, Mukhopadhyay, Subhas, Series Editor, Ning, Cun-Zheng, Series Editor, Nishida, Toyoaki, Series Editor, Pascucci, Federica, Series Editor, Qin, Yong, Series Editor, Seng, Gan Woon, Series Editor, Speidel, Joachim, Series Editor, Veiga, Germano, Series Editor, Wu, Haitao, Series Editor, Zhang, Junjie James, Series Editor, Zhao, Pengfei, editor, Ye, Zhuangzhi, editor, Xu, Min, editor, and Yang, Li, editor

Published
2020
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15. Design and Implementation of Salary Management System for Printing Enterprises

Author

Huo, Yuke, Yang, Wenjie, Ran, Peipei, Guo, Chunli, Liu, Yanxing, Yang, Ge, Cao, Shaozhong, Angrisani, Leopoldo, Series Editor, Arteaga, Marco, Series Editor, Panigrahi, Bijaya Ketan, Series Editor, Chakraborty, Samarjit, Series Editor, Chen, Jiming, Series Editor, Chen, Shanben, Series Editor, Chen, Tan Kay, Series Editor, Dillmann, Rüdiger, Series Editor, Duan, Haibin, Series Editor, Ferrari, Gianluigi, Series Editor, Ferre, Manuel, Series Editor, Hirche, Sandra, Series Editor, Jabbari, Faryar, Series Editor, Jia, Limin, Series Editor, Kacprzyk, Janusz, Series Editor, Khamis, Alaa, Series Editor, Kroeger, Torsten, Series Editor, Liang, Qilian, Series Editor, Martin, Ferran, Series Editor, Ming, Tan Cher, Series Editor, Minker, Wolfgang, Series Editor, Misra, Pradeep, Series Editor, Möller, Sebastian, Series Editor, Mukhopadhyay, Subhas, Series Editor, Ning, Cun-Zheng, Series Editor, Nishida, Toyoaki, Series Editor, Pascucci, Federica, Series Editor, Qin, Yong, Series Editor, Seng, Gan Woon, Series Editor, Speidel, Joachim, Series Editor, Veiga, Germano, Series Editor, Wu, Haitao, Series Editor, Zhang, Junjie James, Series Editor, Zhao, Pengfei, editor, Ouyang, Yun, editor, Xu, Min, editor, Yang, Li, editor, and Ren, Yuhui, editor

Published
2019
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16. Design and Development of Network Printing Exhibition

Author

Liu, Yanxing, Lian, Yusheng, Jin, Yang, Hu, Xiaojie, Xiong, Zhuangzhuang, Angrisani, Leopoldo, Series Editor, Arteaga, Marco, Series Editor, Panigrahi, Bijaya Ketan, Series Editor, Chakraborty, Samarjit, Series Editor, Chen, Jiming, Series Editor, Chen, Shanben, Series Editor, Chen, Tan Kay, Series Editor, Dillmann, Rüdiger, Series Editor, Duan, Haibin, Series Editor, Ferrari, Gianluigi, Series Editor, Ferre, Manuel, Series Editor, Hirche, Sandra, Series Editor, Jabbari, Faryar, Series Editor, Jia, Limin, Series Editor, Kacprzyk, Janusz, Series Editor, Khamis, Alaa, Series Editor, Kroeger, Torsten, Series Editor, Liang, Qilian, Series Editor, Martin, Ferran, Series Editor, Ming, Tan Cher, Series Editor, Minker, Wolfgang, Series Editor, Misra, Pradeep, Series Editor, Möller, Sebastian, Series Editor, Mukhopadhyay, Subhas, Series Editor, Ning, Cun-Zheng, Series Editor, Nishida, Toyoaki, Series Editor, Pascucci, Federica, Series Editor, Qin, Yong, Series Editor, Seng, Gan Woon, Series Editor, Speidel, Joachim, Series Editor, Veiga, Germano, Series Editor, Wu, Haitao, Series Editor, Zhang, Junjie James, Series Editor, Zhao, Pengfei, editor, Ouyang, Yun, editor, Xu, Min, editor, Yang, Li, editor, and Ren, Yuhui, editor

Published
2019
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23. Few-Shot Object Detection in Remote-Sensing Images via Label-Consistent Classifier and Gradual Regression

Author

Liu, Yanxing, Pan, Zongxu, Yang, Jianwei, Zhang, Bingchen, Zhou, Guangyao, Hu, Yuxin, and Ye, Qixiang

Abstract

With the abomination of time-consuming or even impractical large-scale labeling, few-shot object detection (FSOD) based on natural scenes has attracted extensive attention. However, directly migrating FSOD methods designed for natural images to large-size remote-sensing images (RSIs) still remains a challenge. 1) Labels of novel instances within the base dataset are inconsistently assigned between the base training and the few-shot fine-tuning stage, which confuses the detector and leads to significant performance degradation over novel classes. 2) The region proposal network (RPN) of detectors cannot provide sufficient high-quality proposals for remote-sensing objects with various aspect ratios and irregular shapes, leading to decreased detection performance. To tackle these issues, we specify a novel few-shot object detector for RSIs, to avoid the significant performance degradation caused by inconsistent labeling assignments, as well as efficiently leveraging the novel instances that existed in the base dataset. Furthermore, the proposed detector utilizes a coarse-to-fine regression method with an enhanced feature extractor called Gradual RPN to improve the recall of the RPN. Experiments on a newly constructed few-shot detection benchmark show that our approach improves the mAP of novel classes by up to 8.4% and the average recall of the RPN by up to 12.3%. The source code is available at https://github.com/YanxingLiu/SAE-FSDet.

Published
2024
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32. Performance of Mn-Ce-Fe/FA Catalysts on Selective Catalytic Reduction of NO X with CO under Different Atmospheres.

Author

Xia, Zheng, Zhang, Ruiping, Duan, Jixin, Liu, Yanxing, Li, Zhengyuan, and Gou, Xiang

Subjects
CATALYTIC reduction, FLY ash, FLUE gases, WATER vapor, GAS turbines
Abstract

Gas turbines produce a large amount of NOx and CO due to high temperatures and insufficient combustion. Through the selective catalytic reduction of NO with CO (CO-SCR) in a gas turbine, the activities of the Mn-Fe-Ce/FA catalyst using fly ash (FA) as a carrier under different atmospheres were studied. The catalysts prepared by calcining different active materials under different atmospheres were used to analyze their denitrification abilities and resistance to water vapor. The denitrification performance of the catalyst prepared under reducing atmosphere is about 30 percent higher than that of the catalyst prepared under air atmosphere, and the decarburization performance is about 40 percent higher. In the presence of oxygen, the denitrification rate and decarburization rate of the 1:1 ratio of the Mn-Ce catalyst reach 67.16% and 59.57%, respectively. In an oxygen-containing atmosphere, the catalyst prepared by replacing Ce with Fe shows better denitrification and decarburization performances, which are 78.56% and 78.39%, respectively. When the flue gas space velocity is 4000 h−1 and the carbon-nitrogen ratio is 1.6, the catalyst shows better performance. After the water vapor is introduced, the denitrification and decarbonization rates of the catalyst decrease by about 10% and 9%, respectively. After ceasing water vapor, it rebounds by about 8%, and the activity could not be fully restored. However, the catalyst still shows strong water resistance in general. [ABSTRACT FROM AUTHOR]

Published
2023
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35. Reconstructing experience in ancient Rome and Chang'an : a comparative approach

Author

Liu, Yanxing

Abstract

Using comparative approach, this present thesis explores the potential of comparison in the study of ancient capital cities and their residents’ living experience. Although Rome and Chang’an have received a great deal of attention respectively, little work has been done to compare these two capital cities. This neglect is intriguing given the fact that scholars were enthusiastic about comparing the Roman Empire and the Han Empire, two powerful regimes siting on the opposite ends of Eurasia. While most scholarship has been focusing on comparing the rise and fall of empires, the military systems, and the management of territories, the thesis analyzes the capital cities and their differences. Another similar problem that this thesis tries to tackle is the neglect of marginalized people’s living experience in great cities. Non-elite people made up most of the urban population, but the scarcity of evidence prevents us from understanding their daily life. Therefore, the thesis applies Henri Lefebvre’s theory of spatial triad to access the non-elite people’s living experience in two selected places: the Porta Esquilina in Rome and the Xuanping Gate in Chang’an. City gates could offer best available material evidence for the purpose of this thesis. The research carried out in the thesis reveals that non-elite people’s living experience in these two distinct cities might be surprisingly similar.

Published
2022
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41. Study of Color Rendering Evaluation Method of Light Sources for Printing Matter

Author

Jin Yang, Lian Yusheng, Hu Xiaojie, Zilong Liu, Liu Yanxing, Huang Min, Wei Xianfu, and Fangxi Liu

Subjects
Color rendering index, General Computer Science, affinity propagation cluster algorithm, spectral dimension reduction, Computer science, Computer graphics (images), Evaluation methods, Color rendering evaluation, typical color sample sets, General Engineering, General Materials Science, lcsh:Electrical engineering. Electronics. Nuclear engineering, lcsh:TK1-9971
Abstract

Based on the optimization of color samples, we have developed a method to evaluate light sources' color rendering of printing matter. By performing Affinity Propagation (AP) Clustering Algorithm on the color appearance and spectra of the color printing atlas samples printed by a press, two typical color sample sets are obtained. The optimized color sample (OCS) set consists of these two typical color sample sets and it is presented by CMYK dot area coverage. The color rendering indexes (CRIs) CIE-Ra, CRI2012, CIE-Rf of 90 light sources are calculated by taking the OCS set, color printing atlas and standard color sample (SCS) set of CRI as the test color sample (TCS) set. By comparing the Absolute Difference (AD), Mean Absolute Difference (MAD), Coefficient of Variation (CV) and Spearman Correlation Coefficient (SCC) of the CRIs, we find that the indexes calculated by OCS set are closer to these indexes calculated by color printing atlas than by SCS set. Therefore, the OCS set is more suitable for printing applications. After output from a press and measured spectra, the OCS set with CMYK dot area coverage can be used as the TCS set to evaluate the color rendering of light sources for all printing matter output from this press. For proving the reliability of the results, that is, the universality of the OCS set to the presses, the OCS set with fixed CMYK dot area coverage is output from an another press and CRIs are calculated. The results show that OCS set we developed is better than the SCS set. This method can be used for color rendering evaluation of light sources for printing matter.

Published
2020

45. Ultrasound Image Preprocessing Method for Deep-Learning-Based Fatty Liver Diagnosis

Author

Yang Jin, Zilong Liu, Li Lingbo, Yusheng Lian, Chu Yiyang, Zixin Lin, Liu Yanxing, Hu Xiaojie, Guannan He, and Yongle Hu

Subjects
business.industry, Computer science, Noise reduction, Deep learning, Equalization (audio), Preprocessor, Image processing, Pattern recognition, Artificial intelligence, business, Convolutional neural network, Image histogram, Image (mathematics)
Abstract

An iterative image processing method is proposed to improve the performance of Convolutional Neural Network (CNN) model for diagnosing fatty liver. A dataset that contains 17,400 ultrasound images of liver are used in this paper. These liver image samples are preprocessed for noise reduction and texture enhancement firstly. Then the processed image samples are used for training CNN model LeNet-5. According to the accuracy of the trained LeNet-5, the optimal combination of noise reduction and enhancement is obtained. The experimental results show that the accuracy of LeNet-5 model based on original data set is 80.58% and area under the Receiver Operation Characteristic (ROC) Curve value (AUC) is 0.574. And the optimal image processing combination is Butterworth low pass (BLP) and Exposure based Sub Image Histogram Equalization (ESIHE). The model accuracy is 10.01% higher than original data set, and reaches 90.59%. The AUC value of the optimal model has reached 0.845, which is 0.271 higher than the AUC value of the original model. Therefore, iterative image processing is a feasible method to improve the performance of CNN model in diagnosing fatty liver.

Published
2021

48. Improved Spectral Reflectance Reconstruction Algorithm Based on Matrix R Method

Author

Yusheng Lian, Guannan He, Yang Jin, Zixin Lin, Meng Wang, Huang Min, Liu Yanxing, and Hu Xiaojie

Subjects
business.product_category, business.industry, Computer science, Multispectral image, Spectrum (functional analysis), ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION, Pattern recognition, Reconstruction algorithm, Combing, Matrix (mathematics), Artificial intelligence, Chromaticity, business, Smoothing, Digital camera
Abstract

To solve the problem of information loss in multispectral image color reproduction, a new algorithm for reconstructing spectral reflectance is proposed. Based on the traditional matrix R theory, the improved method is obtained by combing ICA and smoothing pseudo-inverse method. We choose the standard color target Color Checker 24 and IT8.7/4 as training and test samples respectively and design the reconstruction experiment. By calculating the spectrum and chromaticity accuracy of ICA, the traditional matrix R and the proposed method, the effect of the new algorithm is verified. The results show that the improved method’s spectrum error and chromaticity error of the training and test color samples are significantly lower than the other two methods. That is, the proposed method improves the spectral information loss of the reconstructed spectrum in the spectral image acquisition system of the multichannel digital camera. It has important significance for solving the problem of mesmerism, and realizing the true color reproduction of the object in the changing observation environment.

Published
2020

49. SVAE-WGAN-Based Soft Sensor Data Supplement Method for Process Industry.

Author

Gao, Shiwei, Qiu, Sulong, Ma, Zhongyu, Tian, Ran, and Liu, Yanxing

Abstract

Challenges of process industry, which is characterized as hugeness of process variables in complexity of industrial environment, can be tackled effectively by the use of soft sensor technology. However, how to supplement the dataset with effective data supplement method under harsh industrial environment is a key issue for the enhancement of prediction accuracy in soft-sensing model. Aimed at this problem, a SVAE-WGAN based soft sensor data supplement method is proposed for process industry. Firstly, deep features are extracted with the stacking of the variational autoencoder (SVAE). Secondly, a generation model is constructed with the combination of stacked variational autoencoder (SVAE) and Wasserstein generative adversarial network (WGAN). Thirdly, the proposed model is optimized with training of dataset in industrial process. Finally, the proposed model is evaluated with abundant experimental tests in terms of MSE, RMSE and MAE. It is shown in the results that the proposed SVAE-WGAN generation network is significantly better than that of the traditional VAE, GAN and WGAN generation network in case of industrial steam volume dataset. Specially, the proposed method is more effective than the latest reference VA-WGAN generation network in terms of RMSE, which is enhanced about 9.08% at most. Moreover, the prediction precision of soft sensors could be improved via the supplement of the training samples. [ABSTRACT FROM AUTHOR]

Published
2022
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