Article
Computer Science, Information Systems
Jiawei Tian, Botao Ma, Siyu Lu, Bo Yang, Shan Liu, Zhengtong Yin
Summary: This study introduces a binocular stereo vision-based 3D reconstruction technique to address challenges in the field of surgical robot navigation. By proposing an innovative stereoscopic endoscopic image correction algorithm and utilizing disparity maps from cardiac soft tissue images, the study achieves precise 3D point acquisition and complex surface reconstruction. The experimental results confirm the accuracy of the calibration algorithm and the effectiveness of the image rectification algorithm in stereo matching. This 3D reconstruction technique shows potential for clinical applications, improving surgical precision and outcomes in cardiac interventions.
Article
Mathematics
Rui Wang, Lisheng Wei, Zhengyan Gu, Xiaohui Liu
Summary: This study proposes an improved matching cost calculation method for reconstructing shoe soles in three dimensions, which utilizes a binocular vision platform and Zhang's calibration method to obtain calibration parameters. The method combines Census and BT costs to calculate the matching cost and optimizes the disparity map through left-right consistency detection and median filtering, resulting in a complete reconstructed sole point cloud contour.
Article
Computer Science, Artificial Intelligence
Xin Tian, Rui Liu, Zhongyuan Wang, Jiayi Ma
Summary: A novel 3D reconstruction method combining polarization imaging and binocular stereo vision has been proposed, which aims to improve accuracy by correcting azimuth angle errors and utilizing low-rank matrix factorization constraints. Experimental results demonstrate the efficiency of the method and its wide application prospects in 3D reconstruction.
INFORMATION FUSION
(2022)
Article
Chemistry, Analytical
Huaizhou Li, Shuaijun Wang, Zhenpeng Bai, Hong Wang, Sen Li, Shupei Wen
Summary: Thermal infrared imaging is less affected by lighting conditions and smoke compared to visible light imaging. However, the lower resolution and lack of rich texture details in thermal infrared images make them unsuitable for stereo matching and 3D reconstruction. To address this issue, we propose an advanced stereo matching algorithm that enhances the quality of infrared stereo imaging. The algorithm includes preprocessing, camera calibration, and disparity map generation using the SGBM algorithm, resulting in improved stereo matching accuracy and practical value for thermal infrared imaging.
Article
Engineering, Multidisciplinary
YongCan Shuang, ZhenZhou Wang
Summary: This paper proposes a new stereo vision matching method and pattern extraction method, which can reconstruct the 3D shape of objects more robustly compared to existing methods. The proposed approach also shows robust reconstruction of dynamic shape movements.
Article
Optics
Yue Wang, Xueyou Han, Jing Rui, Hailan Zhang, Lei Yin, Xuefeng Zhang, Xiangjun Wang
Summary: This paper presents a method for 3D reconstruction of a mobile binocular stereo vision based on push-broom line structured light for a workpiece surface. By extracting subpixel coordinates of the light strip centers and using a relative pose optimization method, the entire surface can be reconstructed in 3D. Experimental results demonstrate the high accuracy and repeatability of the proposed method.
JOURNAL OF THE OPTICAL SOCIETY OF AMERICA A-OPTICS IMAGE SCIENCE AND VISION
(2023)
Article
Engineering, Electrical & Electronic
Hongjun Zhao, Bin Wu
Summary: This paper introduces the application of 5G virtual reality technology in facial image matching and modeling. Images are collected and corrected using a binocular stereo vision system, and a graph cut matching method is used to obtain multi-angle facial disparity maps. Additionally, a building virtual roaming system based on MFC and OpenGL is developed, and experiments demonstrate the high accuracy of the algorithm.
INTERNATIONAL JOURNAL OF COMMUNICATION SYSTEMS
(2022)
Article
Engineering, Electrical & Electronic
Haoxi Cong, Yuxuan Wang, Dong Han, Lipan Qiao, Shengyao Wang, Weijia Zhao, Qingmin Li
Summary: This study built a 3D reconstruction experimental platform based on binocular stereo vision to accurately obtain physical parameters of the secondary arc. The secondary arc image was processed using a dehazing algorithm and a double-threshold recovery algorithm, and the 3D image of the secondary arc was successfully reconstructed based on the optimized disparity map. The results showed spatial differences in the shape changes of the secondary arc, with variations in arc length and diameter divided into two stages. Compared to previous work, this study achieved more realistic 3D reconstruction of the secondary arc, providing a reference for exploring its physical characteristics.
IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT
(2023)
Article
Computer Science, Artificial Intelligence
Ou Jing, Zou Lai, Wan Qinghong, Liu Xin, Li Yingjie
Summary: A measurement approach for weld-seam identification and model reconstruction of remanufacturing blades based on self-developed binocular vision system is proposed in this work, aiming to improve the machining quality and efficiency of the remanufactured parts. The method shows obvious advantages in calculation efficiency and reconstruction accuracy of theoretical machining model compared with traditional measurement methods.
ADVANCED ENGINEERING INFORMATICS
(2021)
Article
Computer Science, Artificial Intelligence
Hui Wei, Lingjiang Meng
Summary: This study proposes a matching algorithm that combines segment and edge matching to improve the accuracy of stereo matching algorithms in binocular vision. By simulating the mechanism of biological vision, the algorithm transforms pixel matching to pixel segment matching and edge matching, reducing time complexity. It can be implemented in an industrial robot environment for high-precision needle threading guidance.
PATTERN RECOGNITION
(2023)
Article
Chemistry, Analytical
Dabao Lao, Yukai Wang, Fang Wang, Chao Gao
Summary: This study presents a calibration method for laser 3D projection systems based on binocular vision, which is proven to be simple, efficient, and accurate.
Article
Optics
Junchao Zhu, Qi Zeng, Fangfang Han, Chang Jia, Yongxin Bian, Chenhong Wei
Summary: Binocular stereo vision is crucial for intelligent driving as it provides image and spatial information. However, environmental disturbances often lead to misalignment in binocular stereo matching, hindering accurate 3D reconstruction. This paper presents an active imaging perception and target measurement method that combines laser scanning and binocular vision. Experimental results show that the proposed method effectively matches binocular images and provides accurate three-dimensional information. The system also has potential applications in autonomous systems due to the advantages of laser line intensity feature matching.
Article
Engineering, Civil
Deyu Li, Longfei Xiao, Handi Wei, Jun Li, Mingyue Liu
Summary: This paper proposes a stereo imaging method for the spatial-temporal measurement of waves in the laboratory. By comparing with traditional probes, the feasibility and accuracy of the method are verified. Experimental results show that this method can efficiently and accurately measure the spatial-temporal field of waves, offering potential for measuring more complex wave fields in nonlinear wave-structure interactions.
COASTAL ENGINEERING
(2022)
Article
Optics
Zhilong Su, Jiyu Pan, Lei Lu, Meiling Dai, Xiaoyuan He, Dongsheng Zhang
Summary: A novel refractive stereo-DIC method is proposed in this work to accurately reconstruct the true shape of submerged objects by considering light refraction. Experimental results show the feasibility and correctness of this approach, indicating its potential to extend stereo-DIC to fluid-immersed 3D deformation characterization.
Article
Engineering, Multidisciplinary
Cheng Yuan, Bing Xiong, Xiuquan Li, Xiaohan Sang, Qingzhao Kong
Summary: A new vision-based damage assessment method for reinforced concrete structures using an intelligent inspection robot and Internet of things-enabled data communication system is proposed in this article to improve the efficiency and safety of infrastructure maintenance. By reconstructing the structure in 3D and using a new deep-learning technique, the proposed system can accurately segment, localize, and quantify damage.
STRUCTURAL HEALTH MONITORING-AN INTERNATIONAL JOURNAL
(2022)
Article
Engineering, Biomedical
Bo Yang, Yiyang Li, Wenfeng Zheng, Zhengtong Yin, Mingzhe Liu, Lirong Yin, Chao Liu
Summary: This work aims to predict the 3D coordinates of the point of interest (POI) on the surface of beating heart in dynamic minimally invasive surgery, using deep learning technique, to improve the manoeuvrability and expand functions of cardiac surgical robots.
BIOMEDICAL SIGNAL PROCESSING AND CONTROL
(2023)
Article
Computer Science, Information Systems
Xiner Liu, Jianshu He, Mingzhe Liu, Zhengtong Yin, Lirong Yin, Wenfeng Zheng
Summary: Amid the rapid advancement of neural machine translation, the challenge of data sparsity has been a major obstacle. This study proposes a general data augmentation technique to address this issue, which improves the pseudo-parallel corpus generated by the reverse translation method and includes a grammar error correction module for low-resource scenarios.
Article
Computer Science, Information Systems
Runxi Liu, Haoran Liu, Bo Yang, Borui Gu, Zhengtong Yin, Shan Liu
Summary: The present study introduces the heterogeneous quasi-continuous spiking cortical model (HQC-SCM) method as a novel approach for neutron and gamma-ray pulse shape discrimination. The method utilizes specific neural responses to extract features in the falling edge and delayed fluorescence parts of radiation pulse signals. As HQC-SCM is a chaotic system, a genetic algorithm-based parameter optimization method was proposed to locate local optima of HQC-SCM's parameter solutions efficiently and robustly.
Article
Energy & Fuels
Wei Dang, Shengjun Liao, Bo Yang, Zhengtong Yin, Mingzhe Liu, Lirong Yin, Wenfeng Zheng
Summary: The prediction ability of traditional machine learning models for battery life is limited. When predicting the remaining useful life (RUL) of multiple batteries, the performance of traditional machine learning is not satisfactory. This paper introduces Gaussian process regression and improves the codec fusion method for multi-step prediction. The Savitzky-Golay method is used to smooth the training set, and a new kernel function is designed to enhance accuracy. The method of dynamic weights is adopted to minimize accumulated error. Experimental results demonstrate that the fusion prediction method effectively reduces cumulative prediction error and accurately predicts RUL of zinc-ion batteries.
JOURNAL OF ENERGY STORAGE
(2023)
Article
Geosciences, Multidisciplinary
Xin Chen, Mingzhe Liu, Dongfen Li, Jiaru Jia, Aiqing Yang, Wenfeng Zheng, Lirong Yin
Summary: Landslide detection is crucial for disaster management and prevention. With the use of multi-channel optical remote sensing technology and the adoption of Conv-Trans Dual Network (CTDNet) based on Swin-Unet, accurate detection of landslides has become more accessible. Experimental results show that CTDNet outperforms other models currently applied in landslide detection.
FRONTIERS IN EARTH SCIENCE
(2023)
Article
Chemistry, Physical
Xuedi Qin, Huanyang Wu, Ruihang Wang, Liang Wang, Lu Liu, Hangjie Li, Bo Yang, Hang Zhou, Zuwei Liao, Feng-Shou Xiao
Summary: This study developed a reaction process that utilizes CoS-1 catalyst and MnOx @ Na2WO4 for the dehydrogenation of ethane and selective hydrogen combustion, thereby improving the conversion of ethane and the selectivity of ethylene. The process resulted in a per-pass ethane conversion rate of 43.2% and ethylene selectivity of 93.1% at 590 degrees Celsius and 0.8 bar of ethane feed.
Article
Environmental Studies
Xuan Liu, Zehao Li, Xinyi Fu, Zhengtong Yin, Mingzhe Liu, Lirong Yin, Wenfeng Zheng
Summary: This study uses NPP-VIIRS NTL data and Landsat 8 OLT images to estimate housing vacancy rates in the Pearl River Delta (PRD) region and tracks their spatial-temporal dynamics. The findings show that despite an overall decrease in housing vacancy rates in the PRD, speculation and irrational real estate investment still exist in cities on the west bank of the Pearl River Estuary and in some isolated districts in other cities. Moreover, increasing proportions of vacant pixels in most cities indicate a rise in real estate development, calling for further supervision.
Article
Humanities, Multidisciplinary
Xuan Liu, Tianyi Shi, Guohui Zhou, Mingzhe Liu, Zhengtong Yin, Lirong Yin, Wenfeng Zheng
Summary: The computational identification and categorization of opinions in text is crucial for providing better understanding and services to online users. However, the current multi-label automatic classification is still inadequate. This study proposes a modified MLkNN classifier that considers both in-sentence and adjacent sentence features, resulting in improved accuracy and speed in emotion classification for short texts on Twitter.
HUMANITIES & SOCIAL SCIENCES COMMUNICATIONS
(2023)
Article
Biodiversity Conservation
Zhengtong Yin, Zhixin Liu, Xuan Liu, Wenfeng Zheng, Lirong Yin
Summary: This study investigates the variation pattern and spatial distribution characteristics of urban heat islands in New York State. The results show that the surface temperature in the study area has slowly increased over the past 20 years, with the heat island effect being particularly obvious from May to October. The expansion of the city has led to an increase in the discomfort index for residents, with 50% of people feeling uncomfortable with the heat. The findings emphasize the need to address the impact of climate change and urban heat islands on human discomfort and improve cities' livability.
ECOLOGICAL INDICATORS
(2023)
Article
Biodiversity Conservation
Lirong Yin, Lei Wang, Barry D. Keim, Kory Konsoer, Zhengtong Yin, Mingzhe Liu, Wenfeng Zheng
Summary: This research used wavelet coherence analysis to examine the relationship between dam operation and river discharge rates, as well as precipitation along the Yangtze River. The analysis revealed strong coherence between dam operation and river discharge rates, and a minor seasonal coherence between dam operation and precipitation. Further studies are needed to understand the reasons for this coherence and its impact on other factors like soil moisture, groundwater levels, air humidity, and the monsoon.
ECOLOGICAL INDICATORS
(2023)
Article
Computer Science, Artificial Intelligence
Wenfeng Zheng, Gu Gong, Jiawei Tian, Siyu Lu, Ruiyang Wang, Zhengtong Yin, Xiaolu Li, Lirong Yin
Summary: In this paper, a Chinese generative dialogue system based on the Transformer model is designed. By improving the relative position coding and self-attention calculation formula, the system performs better in language generation and long-distance attention.
INTERNATIONAL JOURNAL OF COMPUTATIONAL INTELLIGENCE SYSTEMS
(2023)
Article
Computer Science, Information Systems
Jiawei Tian, Botao Ma, Siyu Lu, Bo Yang, Shan Liu, Zhengtong Yin
Summary: This study introduces a binocular stereo vision-based 3D reconstruction technique to address challenges in the field of surgical robot navigation. By proposing an innovative stereoscopic endoscopic image correction algorithm and utilizing disparity maps from cardiac soft tissue images, the study achieves precise 3D point acquisition and complex surface reconstruction. The experimental results confirm the accuracy of the calibration algorithm and the effectiveness of the image rectification algorithm in stereo matching. This 3D reconstruction technique shows potential for clinical applications, improving surgical precision and outcomes in cardiac interventions.
Article
Engineering, Biomedical
Wenwen Wu, Yanqi Huang, Xiaomei Wu
Summary: In this study, a 2D deep learning classification network SRT was proposed to improve automatic ECG analysis. The model structure was enhanced with the CNN and Transformer-encoder modules, and a novel attention module and Dilated Stem structure were introduced to improve feature extraction. Comparative experiments showed that the proposed model outperformed several advanced methods.
BIOMEDICAL SIGNAL PROCESSING AND CONTROL
(2024)
Article
Engineering, Biomedical
Chiheb Jamazi, Ghaith Manita, Amit Chhabra, Houssem Manita, Ouajdi Korbaa
Summary: In this study, a new dynamic and intelligent clustering method for brain tumor segmentation is proposed by combining the improved Aquila Optimizer (AO) and the K-Means algorithm. The proposed MAO-Kmeans approach aims to automatically extract the correct number and location of cluster centers and the number of pixels in each cluster in abnormal MRI images, and the experimental results demonstrate its effectiveness in improving the performance of conventional K-means clustering.
BIOMEDICAL SIGNAL PROCESSING AND CONTROL
(2024)
Article
Engineering, Biomedical
Alberto Hernando, Maria Dolores Pelaez-Coca, Eduardo Gil
Summary: This study applied a new algorithm to decompose the photoplethysmogram (PPG) pulse and identified changes in PPG pulse morphology due to pressure. The results showed that there was an increase in amplitude, width, and area values of the PPG pulse, and a decrease in ratios when pressure increased, indicating vasoconstriction. Furthermore, some parameters were found to be related to the pulse-to-pulse interval.
BIOMEDICAL SIGNAL PROCESSING AND CONTROL
(2024)
Article
Engineering, Biomedical
Jens Moeller, Eveline Popanda, Nuri H. Aydin, Hubert Welp, Iris Tischoff, Carsten Brenner, Kirsten Schmieder, Martin R. Hofmann, Dorothea Miller
Summary: In this study, a method based on texture features is proposed, which can classify healthy gray and white matter against glioma degrees 4 samples with reasonable classification performance using a relatively low number of samples for training. The method achieves high classification performance without the need for large datasets and complex machine learning approaches.
BIOMEDICAL SIGNAL PROCESSING AND CONTROL
(2024)
Article
Engineering, Biomedical
Amrutha Bhaskaran, Manish Arora
Summary: The study evaluates a cyclic repetition frequency-based algorithm for fetal heart rate estimation. The algorithm improves accuracy and reliability for poor-quality signals and performs well for different gestation weeks and clinical settings.
BIOMEDICAL SIGNAL PROCESSING AND CONTROL
(2024)
Article
Engineering, Biomedical
Manan Patel, Harsh Bhatt, Manushi Munshi, Shivani Pandya, Swati Jain, Priyank Thakkar, Sangwon Yoon
Summary: Electroencephalogram (EEG) signals have been effectively used to measure and analyze neurological data and brain-related ailments. Artificial Intelligence (AI) algorithms, specifically the proposed CNN-FEBAC framework, show promising results in studying the EEG signals of autistic patients and predicting their response to stimuli with 91% accuracy.
BIOMEDICAL SIGNAL PROCESSING AND CONTROL
(2024)
Article
Engineering, Biomedical
Wencheng Gu, Kexue Sun
Summary: This research proposes an improved version of YOLOv5 (AYOLOv5) based on the attention mechanism to address the issue of low recognition rate in cell detection. Experimental results demonstrate that AYOLOv5 can accurately identify cell targets and improve the quality and recognition performance of cell pictures.
BIOMEDICAL SIGNAL PROCESSING AND CONTROL
(2024)
Article
Engineering, Biomedical
Anita Gade, V. Vijaya Baskar, John Panneerselvam
Summary: Analysis of exhaled breath is an increasingly used diagnostic technique in medicine. This study introduces a new NICBGM-based model that utilizes various features and weight optimization for accurate data interpretation and result optimization.
BIOMEDICAL SIGNAL PROCESSING AND CONTROL
(2024)
Article
Engineering, Biomedical
Arsalan Asemi, Keivan Maghooli, Fereidoun Nowshiravan Rahatabad, Hamid Azadeh
Summary: Biometric authentication systems can perform identity verification with optimal accuracy in various environments and emotional changes, while the performance of signature verification systems can be affected when people are under stress. This study examines the performance of a signature verification system based on muscle synergy patterns as biometric characteristics for stressed individuals. EMG signals from hand and arm muscles were recorded and muscle synergies were extracted using Non-Negative Matrix Factorization. The extracted patterns were classified using Support Vector Machine for authentication of stressed individuals.
BIOMEDICAL SIGNAL PROCESSING AND CONTROL
(2024)
Article
Engineering, Biomedical
Tianjiao Guo, Jie Yang, Qi Yu
Summary: This paper proposes a CNN-based approach for segmenting four typical DR lesions simultaneously, achieving competitive performance. This approach is significant for DR lesion segmentation and has potential in other segmentation tasks.
BIOMEDICAL SIGNAL PROCESSING AND CONTROL
(2024)
Article
Engineering, Biomedical
G. Akilandasowmya, G. Nirmaladevi, S. U. Suganthi, A. Aishwariya
Summary: This study proposes a technique for skin cancer detection and classification using deep hidden features and ensemble classifiers. By optimizing features to reduce data dimensionality and combining ensemble classifiers, the proposed method outperforms in skin cancer classification and improves prediction accuracy.
BIOMEDICAL SIGNAL PROCESSING AND CONTROL
(2024)
Article
Engineering, Biomedical
Tuuli Uudeberg, Juri Belikov, Laura Paeske, Hiie Hinrikus, Innar Liiv, Maie Bachmann
Summary: This article introduces a novel feature extraction method, the in-phase matrix profile (pMP), specifically adapted for electroencephalographic (EEG) signals, for detecting major depressive disorder (MDD). The results show that pMP outperforms Higuchi's fractal dimension (HFD) in detecting MDD, making it a promising method for future studies and potential clinical use for diagnosing MDD.
BIOMEDICAL SIGNAL PROCESSING AND CONTROL
(2024)
Article
Engineering, Biomedical
P. Nancy, M. Parameswari, J. Sathya Priya
Summary: Stroke is the third leading cause of mortality worldwide, and early detection is crucial to avoid health risks. Existing research on disease detection using machine learning techniques has limitations, so a new stroke detection system is proposed. The experimental results show that the proposed method achieves a high accuracy rate in stroke detection.
BIOMEDICAL SIGNAL PROCESSING AND CONTROL
(2024)
Article
Engineering, Biomedical
Shimin Liu, Zhiwen Huang, Jianmin Zhu, Baolin Liu, Panyu Zhou
Summary: In this study, a continuous blood pressure (BP) monitoring method based on random forest feature selection (RFFS) and a gray wolf optimization-gradient boosting regression tree (GWO-GBRT) prediction model was developed. The method extracted features from electrocardiogram (ECG) and photoplethysmography (PPG) signals, and employed RFFS to select sensitive features highly correlated with BP. A hybrid prediction model of gray wolf optimization (GWO) technique and gradient boosting regression tree (GBRT) algorithm was established to learn the relationship between BP and sensitive features. Experimental results demonstrated the effectiveness and advancement of the proposed method.
BIOMEDICAL SIGNAL PROCESSING AND CONTROL
(2024)
Article
Engineering, Biomedical
Weijun Gong, Yurong Qian, Weihang Zhou, Hongyong Leng
Summary: The recognition of dynamic facial expressions is challenging due to various factors, and obtaining discriminative expression features has been difficult. Traditional deep learning networks lack understanding of global and temporal expressions. This study proposes an enhanced spatial-temporal learning network to improve dynamic facial expression recognition.
BIOMEDICAL SIGNAL PROCESSING AND CONTROL
(2024)
