Pub Date : 2024-08-01DOI: 10.1088/1742-6596/2833/1/012012
Xuejiao Luo, Yage Deng, Yunxia Hu, Fangfang Xu, Tong Ye
This study aims at the shortcomings of traditional artificial ground detection methods for Bursapherenchus xylophophilus disease and applies HSV(Hue-Saturation-Value) color model to realize automatic identification of Bursapherenchus xylophophilus disease and determine its degree of disaster.The entire process is divided into forest data collection, image processing, nematode disease identification and grade determination.The study conducted repeated comparisons and adjusted HSV threshold tests to obtain the HSV threshold with optimal recognition results, and then identify Bursaphelenchus xylophophilus disease and calculate its disease severity. This method is simple to operate and has good identification effects. It can also effectively improve the accuracy and efficiency of pine wood nematode diagnosis. It can be widely used in the field of agriculture and forestry to help better complete disease detection and carry out prevention and control measures more accurately, thereby effectively Protect forest natural resources and improve forestry production efficiency.
{"title":"Research on Bursapherenchus Xylophophilus Disease Recognition Based on HSV Space","authors":"Xuejiao Luo, Yage Deng, Yunxia Hu, Fangfang Xu, Tong Ye","doi":"10.1088/1742-6596/2833/1/012012","DOIUrl":"https://doi.org/10.1088/1742-6596/2833/1/012012","url":null,"abstract":"This study aims at the shortcomings of traditional artificial ground detection methods for Bursapherenchus xylophophilus disease and applies HSV(Hue-Saturation-Value) color model to realize automatic identification of Bursapherenchus xylophophilus disease and determine its degree of disaster.The entire process is divided into forest data collection, image processing, nematode disease identification and grade determination.The study conducted repeated comparisons and adjusted HSV threshold tests to obtain the HSV threshold with optimal recognition results, and then identify Bursaphelenchus xylophophilus disease and calculate its disease severity. This method is simple to operate and has good identification effects. It can also effectively improve the accuracy and efficiency of pine wood nematode diagnosis. It can be widely used in the field of agriculture and forestry to help better complete disease detection and carry out prevention and control measures more accurately, thereby effectively Protect forest natural resources and improve forestry production efficiency.","PeriodicalId":16821,"journal":{"name":"Journal of Physics: Conference Series","volume":"73 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142199371","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-08-01DOI: 10.1088/1742-6596/2833/1/012018
Yining Ge, Shikang Chen
Nowadays, with the rapid development of IP network service demand, network construction is also accelerating, IP network is expanding at a higher rate, and gradually moving toward ultra-high speed networks above 40G. In view of the problems of inconsistent IP packet order, random IP packet length and traffic burst brought by the application environment of high traffic, high bandwidth and high concurrency in ultra-high speed IP network, this paper introduces a kind of dynamic balance processing technology of ultra-high speed IP network based on information label. By optimizing the IP processing architecture, a two-level scheduling architecture of multi-board and multi-module is established, and VPN is established in ultra-high speed IP network by using dynamic balance processing technology and order preserving technology to realize high performance IP processing, so as to achieve ultra-high speed data transmission.
如今，随着 IP 网络业务需求的快速发展，网络建设也在不断加快，IP 网络正在以更高的速度扩容，并逐步向 40G 以上的超高速网络迈进。针对超高速 IP 网络高流量、高带宽、高并发的应用环境带来的 IP 包顺序不一致、IP 包长度随机、流量突发等问题，本文介绍了一种基于信息标签的超高速 IP 网络动态平衡处理技术。通过优化 IP 处理架构，建立多板卡、多模块的两级调度架构，利用动态平衡处理技术和保序技术在超高速 IP 网络中建立 VPN，实现高性能 IP 处理，从而实现超高速数据传输。
{"title":"Design and implementation of dynamic balance in ultra-high speed IP network","authors":"Yining Ge, Shikang Chen","doi":"10.1088/1742-6596/2833/1/012018","DOIUrl":"https://doi.org/10.1088/1742-6596/2833/1/012018","url":null,"abstract":"Nowadays, with the rapid development of IP network service demand, network construction is also accelerating, IP network is expanding at a higher rate, and gradually moving toward ultra-high speed networks above 40G. In view of the problems of inconsistent IP packet order, random IP packet length and traffic burst brought by the application environment of high traffic, high bandwidth and high concurrency in ultra-high speed IP network, this paper introduces a kind of dynamic balance processing technology of ultra-high speed IP network based on information label. By optimizing the IP processing architecture, a two-level scheduling architecture of multi-board and multi-module is established, and VPN is established in ultra-high speed IP network by using dynamic balance processing technology and order preserving technology to realize high performance IP processing, so as to achieve ultra-high speed data transmission.","PeriodicalId":16821,"journal":{"name":"Journal of Physics: Conference Series","volume":"29 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142199373","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-08-01DOI: 10.1088/1742-6596/2833/1/012006
Jing Kang, Junshe An, Yan Zhu
The Consultative Committee for Space Data Systems (CCSDS) has adopted quasi-cyclic low-density parity-check (QC-LDPC) codes for use in near-Earth (C2) and deep space (AR4JA) communications. Existing encoder architectures for C2 codes, however, fall short in efficiency for high-throughput applications. This paper introduces a comprehensive approach combining algorithmic and architectural optimizations to enhance hardware usage efficiency (HUE) while offering flexibility. We propose an integrated inter-block and intra-block parallel (IIB-IBP) encoding algorithm that leverages the unique matrix structure to significantly enhance performance. Additionally, a matrix-specific command register pretreatment (MSCRP) technique is developed to effectively handle the special dimensions of the generator matrix. Furthermore, we detail an offline design process for the automated generation of the encoder core’s HDL description, facilitating fine-tuning of encoding parallelism, latency, FPGA resource utilization, and overall throughput. Hardware implementation on a Virtex XC5VLX110T FPGA demonstrates that our encoder reaches an impressive throughput of 10.6 Gb/s with only 2531 LUTs and 1040 FFs, achieving a HUE of 2.97 Mbps/logic unit. This performance marks a 70.6% increase in HUE when compared to state-of-the-art designs.
{"title":"Flexible and High-Efficiency LDPC Encoder Architecture for CCSDS Standard","authors":"Jing Kang, Junshe An, Yan Zhu","doi":"10.1088/1742-6596/2833/1/012006","DOIUrl":"https://doi.org/10.1088/1742-6596/2833/1/012006","url":null,"abstract":"The Consultative Committee for Space Data Systems (CCSDS) has adopted quasi-cyclic low-density parity-check (QC-LDPC) codes for use in near-Earth (C2) and deep space (AR4JA) communications. Existing encoder architectures for C2 codes, however, fall short in efficiency for high-throughput applications. This paper introduces a comprehensive approach combining algorithmic and architectural optimizations to enhance hardware usage efficiency (HUE) while offering flexibility. We propose an integrated inter-block and intra-block parallel (IIB-IBP) encoding algorithm that leverages the unique matrix structure to significantly enhance performance. Additionally, a matrix-specific command register pretreatment (MSCRP) technique is developed to effectively handle the special dimensions of the generator matrix. Furthermore, we detail an offline design process for the automated generation of the encoder core’s HDL description, facilitating fine-tuning of encoding parallelism, latency, FPGA resource utilization, and overall throughput. Hardware implementation on a Virtex XC5VLX110T FPGA demonstrates that our encoder reaches an impressive throughput of 10.6 Gb/s with only 2531 LUTs and 1040 FFs, achieving a HUE of 2.97 Mbps/logic unit. This performance marks a 70.6% increase in HUE when compared to state-of-the-art designs.","PeriodicalId":16821,"journal":{"name":"Journal of Physics: Conference Series","volume":"36 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142199374","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-08-01DOI: 10.1088/1742-6596/2833/1/012010
Zhoujuan Cui, Wenshuo Peng, Yaqiang Zhang, Yiping Duan, Xiaoming Tao
For intelligent transportation systems, accurately forecasting the future trajectories of multiple agents is pivotal. Considering the increased diversity of agents within a scene, in order to capture and model the variations in their appearance, motion status, behavioral patterns, and interrelationships, we propose a simple yet effective framework based on Spatio-Temporal-Interaction Graph Neural Networks. Specifically, a Multi-Class Agent Encoder is meticulously tailored to the specific class of each agent to distill pertinent information from their motion attributes and historical trajectories. Subsequently, a Spatio-Temporal-Interaction Graph Attention Module is constructed to productively represent and learn the complex, dynamic interactions. Finally, a Multimodal Trajectory Generation Module is customized, and a learnable diversity sampling function is introduced to map the features of each agent to a set of potential variables, so as to capture the multimodal distribution of future trajectories. Empirical evaluations on the ETH/UCY and KITTI datasets reveal that our method can efficiently improve the accuracy of trajectory prediction.
{"title":"Spatio-Temporal-Interaction Graph Neural Networks for Multi-Agent Trajectory Prediction","authors":"Zhoujuan Cui, Wenshuo Peng, Yaqiang Zhang, Yiping Duan, Xiaoming Tao","doi":"10.1088/1742-6596/2833/1/012010","DOIUrl":"https://doi.org/10.1088/1742-6596/2833/1/012010","url":null,"abstract":"For intelligent transportation systems, accurately forecasting the future trajectories of multiple agents is pivotal. Considering the increased diversity of agents within a scene, in order to capture and model the variations in their appearance, motion status, behavioral patterns, and interrelationships, we propose a simple yet effective framework based on Spatio-Temporal-Interaction Graph Neural Networks. Specifically, a Multi-Class Agent Encoder is meticulously tailored to the specific class of each agent to distill pertinent information from their motion attributes and historical trajectories. Subsequently, a Spatio-Temporal-Interaction Graph Attention Module is constructed to productively represent and learn the complex, dynamic interactions. Finally, a Multimodal Trajectory Generation Module is customized, and a learnable diversity sampling function is introduced to map the features of each agent to a set of potential variables, so as to capture the multimodal distribution of future trajectories. Empirical evaluations on the ETH/UCY and KITTI datasets reveal that our method can efficiently improve the accuracy of trajectory prediction.","PeriodicalId":16821,"journal":{"name":"Journal of Physics: Conference Series","volume":"29 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142199413","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-08-01DOI: 10.1088/1742-6596/2833/1/012004
Xiuli Ning, Xiaowei Lu, Yingcheng Xu, Zhenduo Fu
It can be seen from the public opinion monitoring that there are many cases of death and injury caused by quality problems of mechanical products, which poses a serious threat to people’s lives. Therefore, it is particularly important to analyze the reliability of mechanical products. This study focuses on active adaptive composite fault tolerant controller (ACFTC) design for nonlinear system with actuator fault. Firstly, a novel iterative learning observer (ILO) is proposed to estimate the early potential fault. And then, the ACFTC approach is proposed in order to obtain desired performance in the faulty case based on the fault estimation information from ILO. Finally, simulation of the flexible joint robot system verifies the validity and applicability of the algorithm.
{"title":"Active Adaptive Composite Fault Tolerant Controller Design For Nonlinear Systems","authors":"Xiuli Ning, Xiaowei Lu, Yingcheng Xu, Zhenduo Fu","doi":"10.1088/1742-6596/2833/1/012004","DOIUrl":"https://doi.org/10.1088/1742-6596/2833/1/012004","url":null,"abstract":"It can be seen from the public opinion monitoring that there are many cases of death and injury caused by quality problems of mechanical products, which poses a serious threat to people’s lives. Therefore, it is particularly important to analyze the reliability of mechanical products. This study focuses on active adaptive composite fault tolerant controller (ACFTC) design for nonlinear system with actuator fault. Firstly, a novel iterative learning observer (ILO) is proposed to estimate the early potential fault. And then, the ACFTC approach is proposed in order to obtain desired performance in the faulty case based on the fault estimation information from ILO. Finally, simulation of the flexible joint robot system verifies the validity and applicability of the algorithm.","PeriodicalId":16821,"journal":{"name":"Journal of Physics: Conference Series","volume":"296 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142199377","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-08-01DOI: 10.1088/1742-6596/2833/1/012013
Pengyu Zhao, Yuan Liu, Xiaoting Zhang
This study presents a method for plaid fabric image retrieval that combines wavelet and SIFT features to address the challenges of accuracy and efficiency in fabric retrieval due to diverse fabric types. The process starts with cropping plaid fabric images and applying histogram equalization to improve brightness and contrast. Texture is enhanced using the Sobel operator, and the Haar wavelet transform extracts image high-frequency components in various directions. Wavelet features are then derived through histogram statistics. The SIFT algorithm is utilized to describe local features by capturing key points and directional information. A codebook aggregates these features from the fabric database, and VLAD encoding generates a vector for the image features, which is further reduced to 256 dimensions via PCA. A similarity-weighted fusion method combines the wavelet and SIFT features, achieving an mAP of 0.67 and an average retrieval time of 1.1 seconds per image. This method significantly enhances plaid fabric retrieval, aiding in fabric design and production.
{"title":"Plaid Fabric Image Retrieval Based on Wavelet Transform and SIFT Features","authors":"Pengyu Zhao, Yuan Liu, Xiaoting Zhang","doi":"10.1088/1742-6596/2833/1/012013","DOIUrl":"https://doi.org/10.1088/1742-6596/2833/1/012013","url":null,"abstract":"This study presents a method for plaid fabric image retrieval that combines wavelet and SIFT features to address the challenges of accuracy and efficiency in fabric retrieval due to diverse fabric types. The process starts with cropping plaid fabric images and applying histogram equalization to improve brightness and contrast. Texture is enhanced using the Sobel operator, and the Haar wavelet transform extracts image high-frequency components in various directions. Wavelet features are then derived through histogram statistics. The SIFT algorithm is utilized to describe local features by capturing key points and directional information. A codebook aggregates these features from the fabric database, and VLAD encoding generates a vector for the image features, which is further reduced to 256 dimensions via PCA. A similarity-weighted fusion method combines the wavelet and SIFT features, achieving an mAP of 0.67 and an average retrieval time of 1.1 seconds per image. This method significantly enhances plaid fabric retrieval, aiding in fabric design and production.","PeriodicalId":16821,"journal":{"name":"Journal of Physics: Conference Series","volume":"36 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142199363","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Serious jamming effect on the communication signal maybe comes from the result of single-frequency jamming which could concentrate energy applying into the transmitted spectra. Usually, the communication signal is covered by the jamming effect. In order to effectively detect the existence of single frequency interference signal or not, the paper presents a frequency domain abnormal phenomena detection method based on adaptive equalization coefficients. The proposed method directly transforms the calculated equalization coefficients into the frequency domain. Then, the existence of strong single-frequency interference signals can be directly detected online by observing the characteristics of the frequency domain. The simulation results show that this method has a good detection effect on strong single frequency jamming. The research shows that the mentioned detection method and the related anomaly recognition technology based on equalization coefficients can be used for jamming detection, and can provide a new technical approach for jamming detection.
{"title":"Strong Single Frequency Jamming Detection Method based on Adaptive Equalization Coefficients","authors":"Yanhui Qi, Xiaolu Yan, Weican Meng, Qingju He, Guangluan Xu, Xiao Deng","doi":"10.1088/1742-6596/2833/1/012003","DOIUrl":"https://doi.org/10.1088/1742-6596/2833/1/012003","url":null,"abstract":"Serious jamming effect on the communication signal maybe comes from the result of single-frequency jamming which could concentrate energy applying into the transmitted spectra. Usually, the communication signal is covered by the jamming effect. In order to effectively detect the existence of single frequency interference signal or not, the paper presents a frequency domain abnormal phenomena detection method based on adaptive equalization coefficients. The proposed method directly transforms the calculated equalization coefficients into the frequency domain. Then, the existence of strong single-frequency interference signals can be directly detected online by observing the characteristics of the frequency domain. The simulation results show that this method has a good detection effect on strong single frequency jamming. The research shows that the mentioned detection method and the related anomaly recognition technology based on equalization coefficients can be used for jamming detection, and can provide a new technical approach for jamming detection.","PeriodicalId":16821,"journal":{"name":"Journal of Physics: Conference Series","volume":"3 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142199412","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-08-01DOI: 10.1088/1742-6596/2833/1/011002
All papers published in this volume have been reviewed through processes administered by the Editors. Reviews were conducted by expert referees to the professional and scientific standards expected of a proceedings journal published by IOP Publishing.• Type of peer review: Double Anonymous• Conference submission management system: Morressier• Number of submissions received: 41• Number of submissions sent for review: 28• Number of submissions accepted: 27• Acceptance Rate (Submissions Accepted / Submissions Received × 100): 65.9• Average number of reviews per paper: 2.8518518518518516• Total number of reviewers involved: 11• Contact person for queries:Name: Cici ChouEmail: cici@apise.orgAffiliation: Sichuan University
{"title":"Peer Review Statement","authors":"","doi":"10.1088/1742-6596/2833/1/011002","DOIUrl":"https://doi.org/10.1088/1742-6596/2833/1/011002","url":null,"abstract":"All papers published in this volume have been reviewed through processes administered by the Editors. Reviews were conducted by expert referees to the professional and scientific standards expected of a proceedings journal published by IOP Publishing.• <bold>Type of peer review:</bold> Double Anonymous• <bold>Conference submission management system:</bold> Morressier• <bold>Number of submissions received:</bold> 41• <bold>Number of submissions sent for review:</bold> 28• <bold>Number of submissions accepted:</bold> 27• <bold>Acceptance Rate (Submissions Accepted / Submissions Received × 100):</bold> 65.9• <bold>Average number of reviews per paper:</bold> 2.8518518518518516• <bold>Total number of reviewers involved:</bold> 11• <bold>Contact person for queries:</bold><bold>Name:</bold> Cici Chou<bold>Email:</bold> cici@apise.org<bold>Affiliation:</bold> Sichuan University","PeriodicalId":16821,"journal":{"name":"Journal of Physics: Conference Series","volume":"26 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142199414","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-08-01DOI: 10.1088/1742-6596/2833/1/012014
Dong Zhu, Haiyan Zhu
In the training and competition process of athletes, their bodies are subjected to various levels of load and stress. As an important diagnostic tool, ECG signals can provide deep insights into the cardiac function of athletes, including heart rate, rhythm, and changes in cardiac electrical activity. By conducting a thorough examination of ECG readings, we are able to quickly identify possible heart conditions or irregularities, which is essential for preserving the heart health of athletes. However, ECG signals are highly complex and multidimensional. To accurately classify these signals, it is necessary to select the most representative and discriminative features. However, this is not an easy task, and the selection of effective features remains a pressing issue. To address this problem, this paper proposes the CSNet classification network model. This framework eradicates disruptions in electrocardiogram signals, performs attribute extraction via a direct network configuration, and combines channel focus mechanisms and spatial focus mechanisms to enhance attribute representation and categorization capabilities. Furthermore, to retain the temporal information of ECG signals, we introduce the Gated Recurrent Unit (GRU), which helps to better capture temporal patterns and dependencies in the signals, thus enabling more accurate classification of ECG signals.
{"title":"Study on ECG Signal Classification and Athlete Health Analysis Based on Attention Mechanism","authors":"Dong Zhu, Haiyan Zhu","doi":"10.1088/1742-6596/2833/1/012014","DOIUrl":"https://doi.org/10.1088/1742-6596/2833/1/012014","url":null,"abstract":"In the training and competition process of athletes, their bodies are subjected to various levels of load and stress. As an important diagnostic tool, ECG signals can provide deep insights into the cardiac function of athletes, including heart rate, rhythm, and changes in cardiac electrical activity. By conducting a thorough examination of ECG readings, we are able to quickly identify possible heart conditions or irregularities, which is essential for preserving the heart health of athletes. However, ECG signals are highly complex and multidimensional. To accurately classify these signals, it is necessary to select the most representative and discriminative features. However, this is not an easy task, and the selection of effective features remains a pressing issue. To address this problem, this paper proposes the CSNet classification network model. This framework eradicates disruptions in electrocardiogram signals, performs attribute extraction via a direct network configuration, and combines channel focus mechanisms and spatial focus mechanisms to enhance attribute representation and categorization capabilities. Furthermore, to retain the temporal information of ECG signals, we introduce the Gated Recurrent Unit (GRU), which helps to better capture temporal patterns and dependencies in the signals, thus enabling more accurate classification of ECG signals.","PeriodicalId":16821,"journal":{"name":"Journal of Physics: Conference Series","volume":"17 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142199375","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-08-01DOI: 10.1088/1742-6596/2833/1/012015
Chao Dong, Xi Zhao
In recent years, Convolutional Neural Networks (CNNs) have become an important research direction in the field of building damage assessment. Particularly, deep neural networks based on the U-shaped architecture and skip connections have achieved significant breakthroughs in the task of architectural damage assessment. Despite the impressive performance of CNNs, effectively capturing global and long-range semantic information remains a challenge due to the local nature of their convolutional operations. To address this issue, we propose a novel architectural damage assessment model called Bi-DAUnet, which adopts a BiFormer structure similar to U-Net. In this model, we employ a U-shaped encoder-decoder architecture based on BiFormer and combine it with skip connections to achieve global semantic feature learning. Specifically, we utilize a hierarchical BiFormer with a dual-layer routing attention mechanism as the encoder to extract contextual features of architectural images. In the symmetric decoder, a BiFormer Block is introduced to fuse shallow and deep features of the feature maps and learn the correlation between pixels at distant locations. Experimental results indicate that the U-shaped encoder-decoder network based on BiFormer achieves superior performance in the task of architectural damage assessment compared to fully convolutional methods.
近年来，卷积神经网络（CNN）已成为建筑损伤评估领域的一个重要研究方向。特别是基于 U 型架构和跳接的深度神经网络在建筑损伤评估任务中取得了重大突破。尽管 CNN 的性能令人印象深刻，但由于其卷积操作的局部性，有效捕捉全局和长距离语义信息仍然是一个挑战。为了解决这个问题，我们提出了一种名为 Bi-DAUnet 的新型建筑损坏评估模型，它采用了类似于 U-Net 的 BiFormer 结构。在该模型中，我们采用了基于 BiFormer 的 U 型编码器-解码器架构，并将其与跳转连接相结合，以实现全局语义特征学习。具体来说，我们利用具有双层路由注意机制的分层 BiFormer 作为编码器，提取建筑图像的上下文特征。在对称解码器中，引入 BiFormer Block 来融合特征图的浅层和深层特征，并学习远处像素之间的相关性。实验结果表明，与全卷积方法相比，基于 BiFormer 的 U 型编码器-解码器网络在建筑损坏评估任务中取得了更优越的性能。
{"title":"Bi-DAUnet: Leveraging BiFormer in a Unet-like Architecture for Building Damage Assessment","authors":"Chao Dong, Xi Zhao","doi":"10.1088/1742-6596/2833/1/012015","DOIUrl":"https://doi.org/10.1088/1742-6596/2833/1/012015","url":null,"abstract":"In recent years, Convolutional Neural Networks (CNNs) have become an important research direction in the field of building damage assessment. Particularly, deep neural networks based on the U-shaped architecture and skip connections have achieved significant breakthroughs in the task of architectural damage assessment. Despite the impressive performance of CNNs, effectively capturing global and long-range semantic information remains a challenge due to the local nature of their convolutional operations. To address this issue, we propose a novel architectural damage assessment model called Bi-DAUnet, which adopts a BiFormer structure similar to U-Net. In this model, we employ a U-shaped encoder-decoder architecture based on BiFormer and combine it with skip connections to achieve global semantic feature learning. Specifically, we utilize a hierarchical BiFormer with a dual-layer routing attention mechanism as the encoder to extract contextual features of architectural images. In the symmetric decoder, a BiFormer Block is introduced to fuse shallow and deep features of the feature maps and learn the correlation between pixels at distant locations. Experimental results indicate that the U-shaped encoder-decoder network based on BiFormer achieves superior performance in the task of architectural damage assessment compared to fully convolutional methods.","PeriodicalId":16821,"journal":{"name":"Journal of Physics: Conference Series","volume":"5 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142199366","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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