2022 14th International Conference on Signal Processing Systems (ICSPS)最新文献_第4页

Research on Optimization Algorithm of Low-Resolution Radar Target Recognition Based on Neural Network 基于神经网络的低分辨率雷达目标识别优化算法研究

2022 14th International Conference on Signal Processing Systems (ICSPS) Pub Date : 2022-11-01 DOI: 10.1109/ICSPS58776.2022.00017

Xiaoyan Liu, Renhong Xie, Yongnan Zhou, Zongmin Liu, Weilin Wang, Wang Ziye, Li Peng, Rui Yibin

引用次数: 0

Single Image Clothing Style Recognition Using Mask RCNN 利用掩模RCNN识别单图像服装风格

2022 14th International Conference on Signal Processing Systems (ICSPS) Pub Date : 2022-11-01 DOI: 10.1109/ICSPS58776.2022.00077

Lu Wang, Diming Zhang, Yuanjiang Li, Zhenxing Li

引用次数: 0

A Frequency Invariant Broadband Beamformer Based on Directional Microphone Array 一种基于定向传声器阵列的频不变宽带波束形成器

2022 14th International Conference on Signal Processing Systems (ICSPS) Pub Date : 2022-11-01 DOI: 10.1109/ICSPS58776.2022.00115

Ruidong Fang, Han Xue, Jingbiao Huang, Jucai Lin, Tingwei Chen, Jun Yin, Yapeng Mao, Weizhen Huang

引用次数: 0

Electromagnetic Exposure Aware RSMA for Multiuser Massive MIMO Uplink 面向多用户海量MIMO上行链路的电磁暴露感知RSMA

2022 14th International Conference on Signal Processing Systems (ICSPS) Pub Date : 2022-11-01 DOI: 10.1109/ICSPS58776.2022.00117

Hanyu Jiang, Li You, A. Elzanaty, Jue Wang, Wen Wang, Xiqi Gao, M. Alouini

引用次数: 1

A VQ-VAE Based Recognition Algorithm for Terahertz Security Inspection Images 基于VQ-VAE的太赫兹安检图像识别算法

2022 14th International Conference on Signal Processing Systems (ICSPS) Pub Date : 2022-11-01 DOI: 10.1109/ICSPS58776.2022.00074

Xinyu Zha, Yechao Bai

{"title":"A VQ-VAE Based Recognition Algorithm for Terahertz Security Inspection Images","authors":"Xinyu Zha, Yechao Bai","doi":"10.1109/ICSPS58776.2022.00074","DOIUrl":"https://doi.org/10.1109/ICSPS58776.2022.00074","url":null,"abstract":"Terahertz imaging technology has been used in the field of security inspection due to its excellent perspective ability. However, the terahertz security inspection images have the problem of poor image quality and cannot cover all types of dangerous objects. In this paper, a terahertz image recognition algorithm based on Vector Quantized-Variational Autoencoder (VQ-VAE) is proposed. The algorithm realizes image data enhancement through dynamically learned prior, and discrete potential space is used to efficiently identify abnormal objects outside the training set. In order to improve the network recognition performance, the attention CBAM module is introduced to increase the attention ratio of the key target area. The algorithm embeds Center Loss metric learning module into the network frame to increase the inter-class distance and reduce the intra-class distance, thereby improving the clustering and generalization performance. The experimental verification is carried out on the actual collected terahertz security image data set. The experimental results show that the improved and optimized VQ-VAE image recognition network is significantly better than the convolutional neural network in recognition accuracy and has better generalization ability.","PeriodicalId":330562,"journal":{"name":"2022 14th International Conference on Signal Processing Systems (ICSPS)","volume":"88 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124380218","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

Impact of Extreme Class-Imbalance on Landslide-Risk Prediction and Mitigation Using Two-Stage Deep Neural Network 极端类不平衡对两阶段深度神经网络滑坡风险预测与缓解的影响

2022 14th International Conference on Signal Processing Systems (ICSPS) Pub Date : 2022-11-01 DOI: 10.1109/ICSPS58776.2022.00131

N. Tengtrairat, W. Woo, P. Parathai, C. Sundaranaga, T. Kridakorn, N. Ayutthaya, D. Rinchumphu

{"title":"Impact of Extreme Class-Imbalance on Landslide-Risk Prediction and Mitigation Using Two-Stage Deep Neural Network","authors":"N. Tengtrairat, W. Woo, P. Parathai, C. Sundaranaga, T. Kridakorn, N. Ayutthaya, D. Rinchumphu","doi":"10.1109/ICSPS58776.2022.00131","DOIUrl":"https://doi.org/10.1109/ICSPS58776.2022.00131","url":null,"abstract":"The classification of landslides is the one of the most challenging topics because of the complexity of the relationships of various dynamic and uncertain factors and the physical gaining data processes. Landslide incidents frequently occur in the upper northern region of Thailand due to its topography. The landslide classification method is proposed to capture the significant features from an extreme case of class-imbalance dataset. The imbalanced nature of some real-world data is one of the current challenges for machine learning researchers. A study area of this research covers an area of 25 square kilometers at Chiang Rai, in Thailand which contains 30,408 non-landslide data and 1,077 landslide data. The percentage of landslide data is 3.54% of the total data. This paper proposed the solution of landslide classification given by extreme class-imbalance dataset. The proposed method has two main steps i.e., firstly, mitigating class-imbalance dataset. and secondly two-stage learning. Performance of the proposed method benchmarks the baseline, the logistic regression (LR), the random forest classifier (RFC) methods given by enhanced dataset. In the case of imbalance dataset, the one-class method is assessed against the proposed method along with the LR and the RFC methods. Experimental results demonstrate that the proposed method has improved the landslide-risk prediction performance over the baseline, the LR, the RFC and the one-class SVM methods in terms of an average area under the curve scores by 0.48, 0.48, 0.03, and 0.06, respectively, in both enhanced dataset and imbalance dataset.","PeriodicalId":330562,"journal":{"name":"2022 14th International Conference on Signal Processing Systems (ICSPS)","volume":"145 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130484840","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

A Method for Processing Unwanted Target Caused by Reflection in Secondary Surveillance Radar 二次监视雷达反射产生的无用目标处理方法

2022 14th International Conference on Signal Processing Systems (ICSPS) Pub Date : 2022-11-01 DOI: 10.1109/ICSPS58776.2022.00029

K. D. Do, Loi V. Nguyen, Thanh N. Nguyen, Thang M. Nguyen, Vu T. Tran

引用次数: 0

Continuous Gesture Segmentation Method Based on Micro-Doppler Feature Via Millimeter Wave Radar 基于毫米波雷达微多普勒特征的连续手势分割方法

2022 14th International Conference on Signal Processing Systems (ICSPS) Pub Date : 2022-11-01 DOI: 10.1109/ICSPS58776.2022.00022

Fuyang Liu, Zhaoyang Wang, Yifan Yao, Jingbo Wang, Xiangwei Dang, Zhiyuan Zeng, Xing-dong Liang, Yan-lei Li

{"title":"Continuous Gesture Segmentation Method Based on Micro-Doppler Feature Via Millimeter Wave Radar","authors":"Fuyang Liu, Zhaoyang Wang, Yifan Yao, Jingbo Wang, Xiangwei Dang, Zhiyuan Zeng, Xing-dong Liang, Yan-lei Li","doi":"10.1109/ICSPS58776.2022.00022","DOIUrl":"https://doi.org/10.1109/ICSPS58776.2022.00022","url":null,"abstract":"Gesture recognition technology via millimeter wave radar is an efficient human-computer interaction (HCI) solution with a more significant environmental adaptive capability compared with optical sensors. Gesture segmentation is an essential step in gesture recognition process, and most of the previous work has focused on segmenting fixed-length discrete gestures, while less research has been done on segmentation algorithm for a continuous sequence of variable-length gestures. A gesture segmentation method for variable-length continuous gesture sequences based on micro-Doppler feature is proposed. Particularly, the Bidirectional One-Sided CFAR Algorithm (BOS-CFAR) which is derived from Constant False Alarm Rate Algorithm (CFAR) is skillfully designed to detect valid gesture frames. Then the valid frames is set as growth points and clustering operation is implemented to obtain the approximate segmentation parts of each gesture. Finally, the gesture domain is fine-tuned according to the maximum and minimum micro-Doppler values of neighborhood to achieve the segmentation task of variable-length continuous gestures with over 96.6% recall and nearly 100% precision of six gestures.","PeriodicalId":330562,"journal":{"name":"2022 14th International Conference on Signal Processing Systems (ICSPS)","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131457847","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

Multi-Target Detection Based on Improved CA-CF AR Algorithm 基于改进CA-CF AR算法的多目标检测

2022 14th International Conference on Signal Processing Systems (ICSPS) Pub Date : 2022-11-01 DOI: 10.1109/ICSPS58776.2022.00085

Ruiguang Lv, Jianjiang Zhou, Zhe Xu, Kai Jiang, Yiling Peng

引用次数: 0

A Method of Virtual Array Aperture Extension for FMCW MIMO Phase-Coded Radar 一种FMCW MIMO相位编码雷达虚拟阵列孔径扩展方法

2022 14th International Conference on Signal Processing Systems (ICSPS) Pub Date : 2022-11-01 DOI: 10.1109/ICSPS58776.2022.00018

Cheng Zhang, Gong Zhang

引用次数: 0