Proceedings of the 2023 5th International Symposium on Signal Processing Systems最新文献

High precision reference measurement technology for mechanical scanning radar 机械扫描雷达高精度参考测量技术

Proceedings of the 2023 5th International Symposium on Signal Processing Systems Pub Date : 2023-03-24 DOI: 10.1145/3606193.3606202

Hu Hong, Lei Li

引用次数: 0

An End-to-end Learning Based Covolutional Neural Network for Single Image Defogging Algorithm 基于端到端学习的卷积神经网络单幅图像去雾算法

Proceedings of the 2023 5th International Symposium on Signal Processing Systems Pub Date : 2023-03-24 DOI: 10.1145/3606193.3606196

Qiqing Li, Ru Li, Xi Shen, Wei Lv

{"title":"An End-to-end Learning Based Covolutional Neural Network for Single Image Defogging Algorithm","authors":"Qiqing Li, Ru Li, Xi Shen, Wei Lv","doi":"10.1145/3606193.3606196","DOIUrl":"https://doi.org/10.1145/3606193.3606196","url":null,"abstract":"In the era of big data, there are more and more outdoor camera acquisition equipment. Due to the influence of extreme weather, such as fog, camera acquisition equipment is easy to lead to the decline of image quality and destroy the value of image application. Therefore, this paper will propose an advanced dehazing algorithm to make the foggy image clearer. Based on the principle of residual neural network, combined with attention mechanism and feature pyramid idea, this paper proposes an end to-end learning single image dehazing algorithm. Let the network learn the relationship between channels and pixels, and use the feature pyramid multi-scale fusion feature to restore the foggy image to a clear image. The SSIM score was 0.9687 and the PSNR score was 29.16. Very good results have been achieved on the RESIDE outdoor dataset. This paper finds the scores obtained by testing DCP, AOD-NET, DeHazeNet, and GFN methods on the same dataset. Compared with these four methods, there is a significant improvement. In particular, it is 15.39% higher than the DCP method on SSIM and 10.03% higher on PSNP.","PeriodicalId":292243,"journal":{"name":"Proceedings of the 2023 5th International Symposium on Signal Processing Systems","volume":"51 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125530578","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}

引用次数: 0

Design and Implementation of Target Tracking System in Low Illumination Environment Based on FPGA 基于FPGA的低照度环境下目标跟踪系统设计与实现

Proceedings of the 2023 5th International Symposium on Signal Processing Systems Pub Date : 2023-03-24 DOI: 10.1145/3606193.3606199

Naijie Xin, M. Xie, Jiande Shi, Tiantai Lu, Zhifeng Ma

{"title":"Design and Implementation of Target Tracking System in Low Illumination Environment Based on FPGA","authors":"Naijie Xin, M. Xie, Jiande Shi, Tiantai Lu, Zhifeng Ma","doi":"10.1145/3606193.3606199","DOIUrl":"https://doi.org/10.1145/3606193.3606199","url":null,"abstract":"Object tracking has been an important research topic in the field of computer vision. At present, most target tracking algorithms need to work in an environment with good lighting conditions. Environments such as night, rainy days, and foggy days will cause tracking drift and even target loss. In order to solve the above problems, this design proposes a target tracking system that combines image enhancement algorithm and target tracking algorithm. The image enhancement uses the Multi-Scale Retinex (MSR) algorithm to correct the color and dynamic range of the input image; the target tracking algorithm uses the Meanshift algorithm to track the enhanced image. In order to deploy the algorithm to FPGA for edge computing acceleration, a streaming computing architecture is designed, and at the same time, the algorithm is partially refactored at the design level to better adapt to FPGA deployment; finally, high-level synthesis tools are used, combined with optimization instructions A high-efficiency target tracking system with local parallelization and overall pipeline is designed.","PeriodicalId":292243,"journal":{"name":"Proceedings of the 2023 5th International Symposium on Signal Processing Systems","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129129393","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}

引用次数: 0

Millimeter Wave Radar Fall Detection Algorithm Based on Improved Transformer 基于改进变压器的毫米波雷达跌落检测算法

Proceedings of the 2023 5th International Symposium on Signal Processing Systems Pub Date : 2023-03-24 DOI: 10.1145/3606193.3606195

Zhiqiang Bao, Ting Ai, Jinhang Su

引用次数: 0

Accurate Shadow height measurement technology of the SAR image SAR图像阴影高度精确测量技术

Proceedings of the 2023 5th International Symposium on Signal Processing Systems Pub Date : 2023-03-24 DOI: 10.1145/3606193.3606194

Lei Li, Hu Hong

引用次数: 0

Speech Recognition Method Based on Deep Learning of Artificial Intelligence: An example of BLSTM-CTC model 基于人工智能深度学习的语音识别方法——以BLSTM-CTC模型为例

Proceedings of the 2023 5th International Symposium on Signal Processing Systems Pub Date : 2023-03-24 DOI: 10.1145/3606193.3606201

Kangyu Chen, Zhiyuan Peng

{"title":"Speech Recognition Method Based on Deep Learning of Artificial Intelligence: An example of BLSTM-CTC model","authors":"Kangyu Chen, Zhiyuan Peng","doi":"10.1145/3606193.3606201","DOIUrl":"https://doi.org/10.1145/3606193.3606201","url":null,"abstract":"Under the influence of information, network and intelligent high-speed development situation, China's intelligent technology and other aspects have made great progress and achievements, derived a lot of advanced artificial intelligence technology, machine learning technology and deep learning technology, etc., to promote the development of intelligence and information in major fields. Artificial intelligence deep learning is the fusion of artificial intelligence technology and machine learning technology, which lays the foundation for the reform and innovation of artificial voice intelligent recognition technology and intelligent robot technology. So in order to improve the application level of intelligent speech recognition technology, it is necessary to continuously optimize the speech recognition method based on AI deep learning. In this regard, according to the relevant literature, this paper addresses the problem that phoneme features of varying duration are generated during the propagation of speech signals, and these features affect the correct rate of speech recognition, and the phoneme features of different lengths are standardized based on the deep learning research mentioned in this paper with BLSTM-CTC as an example. By evaluating the model on the Thchs30 and ST-CMDS datasets, the results show that the MCFN-based BLSTM-CTC speech recognition model has a reduced recognition word error rate compared with the traditional speech recognition model.","PeriodicalId":292243,"journal":{"name":"Proceedings of the 2023 5th International Symposium on Signal Processing Systems","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123290054","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}

引用次数: 0

Ornaments and Barlines Recognition of Numbered Musical Notation Using YOLOv5 使用YOLOv5的数字乐谱的装饰物和横线识别

Proceedings of the 2023 5th International Symposium on Signal Processing Systems Pub Date : 2023-03-24 DOI: 10.1145/3606193.3606197

Yan Zhang, Liumei Zhang, Yu-Lan Han

引用次数: 0

Study on Hyperspectral Remote Sensing Images of GF-5 De-Blurring Based on Sparse Representation 基于稀疏表示的GF-5高光谱遥感图像去模糊研究

Proceedings of the 2023 5th International Symposium on Signal Processing Systems Pub Date : 2023-03-24 DOI: 10.1145/3606193.3606198

Hong Wang

{"title":"Study on Hyperspectral Remote Sensing Images of GF-5 De-Blurring Based on Sparse Representation","authors":"Hong Wang","doi":"10.1145/3606193.3606198","DOIUrl":"https://doi.org/10.1145/3606193.3606198","url":null,"abstract":"Deblurring high resolution remote sensing image is a very important problem in remote sensing research. In this paper, we propose a new deblurring algorithm for high-resolution remote sensing images (HSI) based on sparse representation. The purpose of this study is to apply compressed sensing measurement and reconstruction technology to realize the processing of remote sensing image, and discuss the Under what circumstances can CS achieve better results in remote sensing image processing. The algorithm uses fast gradient projection algorithm to achieve deblurring and retain the important ground information of the original image. Experiments on remote sensing images obtained by GF-5 show that the algorithm can filter the blurring of remote sensing images well and improve the peak-to-noise ratio (PSNR) of images. The algorithm has better performance than other sparse representation algorithms. This paper explores the application of dictionary learning theory and sparse decomposition in remote sensing image processing. By further extending the algorithm proposed in this paper and adding new constraints, remote sensing image restoration, target recognition, deblurring, fusion and so on can be carried out.","PeriodicalId":292243,"journal":{"name":"Proceedings of the 2023 5th International Symposium on Signal Processing Systems","volume":"49 4","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121011046","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}

引用次数: 0

Hearing Cyber-Attacks: A Novel Model for Bridging Network Security Situation and Music 听觉网络攻击:一种桥接网络安全状况与音乐的新模型

Proceedings of the 2023 5th International Symposium on Signal Processing Systems Pub Date : 2023-03-24 DOI: 10.1145/3606193.3606204

Yichuan Wang, Yibin Ma, Junxia Ding, Xiang Sun, Dan Wu, X. Hei

{"title":"Hearing Cyber-Attacks: A Novel Model for Bridging Network Security Situation and Music","authors":"Yichuan Wang, Yibin Ma, Junxia Ding, Xiang Sun, Dan Wu, X. Hei","doi":"10.1145/3606193.3606204","DOIUrl":"https://doi.org/10.1145/3606193.3606204","url":null,"abstract":"With the continuous evolution of network attacks, the risks brought by the network are also increasing. In order to enable network administrators to monitor the network situation more easily, quickly and efficiently, and discover security risks such as network anomalies or attacks in a timely manner, this paper proposes a solution about network situation auralization. The novelty of this method lies in that it solves the problems, including high professional requirements, frequent human-computer interaction, and poor situation presentation effect in traditional network security situation visualization, and instead displays the network situation in the form of music. The solution provides two models to be chosen from: one is to use the extracted network traffic data as notes to directly generate music and display it; the other consists of the following procedures: The first step is to calculate and classify the acquired MIDI music collection based on emotional color. The second step requires to slice the extracted network traffic data, performing sampling statistics in different intervals, the network situation of this section is mapped to the corresponding MIDI music collection for music display after analysis.","PeriodicalId":292243,"journal":{"name":"Proceedings of the 2023 5th International Symposium on Signal Processing Systems","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127814293","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}

引用次数: 0

SAR image geometry correction technology based on block parallel signal processing 基于分块并行信号处理的SAR图像几何校正技术

Proceedings of the 2023 5th International Symposium on Signal Processing Systems Pub Date : 2023-03-24 DOI: 10.1145/3606193.3606200

Lei Li, Hui-Sung Hong

引用次数: 0