2023 3rd International Conference on Neural Networks, Information and Communication Engineering (NNICE)最新文献_第6页

Effect of BDS-2 Different Orbiting Satellites on BDS-3 Single-frequency Single Point Positioning Performance 北斗二号不同轨道卫星对北斗三号单频单点定位性能的影响

2023 3rd International Conference on Neural Networks, Information and Communication Engineering (NNICE) Pub Date : 2023-02-24 DOI: 10.1109/NNICE58320.2023.10105769

Hong Zhang, Qinglin Guan, Chunming Fan

引用次数: 0

Face mask detection based on improved YOLOv3 algorithm 基于改进YOLOv3算法的口罩检测

2023 3rd International Conference on Neural Networks, Information and Communication Engineering (NNICE) Pub Date : 2023-02-24 DOI: 10.1109/NNICE58320.2023.10105750

Jie Wu, Lei Wang

{"title":"Face mask detection based on improved YOLOv3 algorithm","authors":"Jie Wu, Lei Wang","doi":"10.1109/NNICE58320.2023.10105750","DOIUrl":"https://doi.org/10.1109/NNICE58320.2023.10105750","url":null,"abstract":"In the current situation of COVID-19 prevention and control, wearing masks remains an important way to prevent the transmission of the Novel Coronavirus. Aiming at the problem that the detection accuracy of the traditional YOLOv3 algorithm can still be improved, this paper proposes an improved yolov3 algorithm and applies it to the practical problem of detecting whether to wear a mask. Firstly, the algorithm introduces the residual structure of structural reparameterization in the feature extraction network named Darknet53 of YOLOv3 to obtain the input features; Secondly, the SimSPPF (Simplified Spatial Pyramid Pooling-Fast) is introduced to enhance feature extraction; Finally, an improved attention mechanism is introduced to make the model focus on regions with more prominent features. Besides, in order to ensure the accuracy of target detection, CIoU and Focal loss function was used in the training process. The results show that compared with the traditional YOLOv3, the detection accuracy of the improved algorithm for normal face and mask face is improved by 16.98% and 7.30% respectively, and the mAP is improved by 12.14%, which can meet the requirements of daily use and lay a foundation for rapid face recognition when wearing mask. (Abstract)","PeriodicalId":263114,"journal":{"name":"2023 3rd International Conference on Neural Networks, Information and Communication Engineering (NNICE)","volume":"65 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130287307","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

Joint Beamforming and Deployment Design for IRS-aided Energy Harvest IoT Network irs辅助能量采集物联网联合波束形成与部署设计

2023 3rd International Conference on Neural Networks, Information and Communication Engineering (NNICE) Pub Date : 2023-02-24 DOI: 10.1109/NNICE58320.2023.10105803

Zhenwei Liu, W. Zhang, Qi Cao, Yunlong Liang, W. Huang, Shiwen He

{"title":"Joint Beamforming and Deployment Design for IRS-aided Energy Harvest IoT Network","authors":"Zhenwei Liu, W. Zhang, Qi Cao, Yunlong Liang, W. Huang, Shiwen He","doi":"10.1109/NNICE58320.2023.10105803","DOIUrl":"https://doi.org/10.1109/NNICE58320.2023.10105803","url":null,"abstract":"In this paper, we propose a transmission design scheme for the simultaneous wireless information and power transfer (SWIPT) in the intelligent reflecting surface (IRS) aided multi-user interference channel (IFC). Our goal is to maximize the harvested energy of all receivers by jointly optimizing the transmit and reflective beamforming vectors as well as the location of the IRSs while guaranteeing the rate of each user, deployable region of each IRS, and total transmit power constraints. The formulated optimization problem is hard to be solved due to the non-convex coupled of the variables related with location and beamforming vectors as well as the infinite number of constraints. To overcome the difficulty, we first design the location of IRSs by decoupling the larger-scale and small-scale fading of the reflective channels with the local region assumption. Then, based on this, we transform the transmit and reflective beamforming optimization problem into the second-order cone program (SOCP) and the relaxed semi-definite program (SDP) problems, which are convex and solved by utilizing the conventional interior point approach. Numerical results report that the gain is improved by optimizing the location of IRSs.","PeriodicalId":263114,"journal":{"name":"2023 3rd International Conference on Neural Networks, Information and Communication Engineering (NNICE)","volume":"67 4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130385990","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

Study on MRI Slices-based Lightweight Neural Network in Alzheimer's Disease Detection 基于MRI切片的轻量级神经网络在阿尔茨海默病检测中的研究

2023 3rd International Conference on Neural Networks, Information and Communication Engineering (NNICE) Pub Date : 2023-02-24 DOI: 10.1109/NNICE58320.2023.10105740

Qiongmin Zhang, Ying Long, Hongshun Cai

{"title":"Study on MRI Slices-based Lightweight Neural Network in Alzheimer's Disease Detection","authors":"Qiongmin Zhang, Ying Long, Hongshun Cai","doi":"10.1109/NNICE58320.2023.10105740","DOIUrl":"https://doi.org/10.1109/NNICE58320.2023.10105740","url":null,"abstract":"Currently, early detection and intervention are still the key to prevent the aggravation of Alzheimer's disease (AD). Computer assisted diagnosis can provide great help for the early detection of AD. However, compared with natural images, medical images are generally difficult to collect and always have small data sets. To solve this problem, we propose a magnetic resonance imaging (MRI) slices-based lightweight neural network to effectively identify AD. In the proposed method, we use ShuffleNet as the backbone network for feature extraction. Efficient channel attention is added to capture the information of cross-channel interaction information. Triplet loss and cross entropy loss in deep metric learning are combined to ensure the multi-slices under the same subject are classified consistently. The experimental results indicate that, compare with state-of-the-art lightweight methods, our model achieves better classification performance with only 1.52M parameters and 5.56G FLOPs. Experiments verify that our method is helpful to reduce the number of parameters, FLOPs and improve the model performance. Through the construction of the model, it is expected to contribute to the improvement of AD intelligent detection on devices with limited computing power.","PeriodicalId":263114,"journal":{"name":"2023 3rd International Conference on Neural Networks, Information and Communication Engineering (NNICE)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128942713","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

YOLO-Owl: An Occlusion Aware Detector for Low Illuminance Environment 低照度环境下的遮挡感知检测器YOLO-Owl

2023 3rd International Conference on Neural Networks, Information and Communication Engineering (NNICE) Pub Date : 2023-02-24 DOI: 10.1109/NNICE58320.2023.10105800

Jiwei Hu, Zhiwei Cui

引用次数: 0

Study on Applying Median Cancellation Adaptive Clutter Suppression Interference Algorithm to Airborne Radar 机载雷达中值对消自适应杂波抑制干扰算法研究

2023 3rd International Conference on Neural Networks, Information and Communication Engineering (NNICE) Pub Date : 2023-02-24 DOI: 10.1109/NNICE58320.2023.10105703

Z. Li, Juan Zhao, Shanshan Lu

{"title":"Study on Applying Median Cancellation Adaptive Clutter Suppression Interference Algorithm to Airborne Radar","authors":"Z. Li, Juan Zhao, Shanshan Lu","doi":"10.1109/NNICE58320.2023.10105703","DOIUrl":"https://doi.org/10.1109/NNICE58320.2023.10105703","url":null,"abstract":"Clutter Suppression Interference (CSI) is a common radar signal processing method, which efficiently suppresses ground clutter interference in radar received echoes and can greatly improve the signal-to-noise ratio of airborne synthetic aperture radar ground motion target indication (SAR/GMTI). However, the implementation of the clutter suppression algorithm in engineering is difficult because of the large number of filtering power coefficients to be calculated in real time. Based on this research background, this paper models the ground clutter of airborne radar, analyzes the principles and performance of three clutter suppression algorithms, CSI, ACSI and median cancellation ACSI, and performs engineering implementation. From the engineering experimental results, it can be seen that all three algorithms can improve the airborne radar signal-to-noise ratio and thus improve the recognition capability of moving targets, among which the median pair cancellation ACSI algorithm has the lowest false alarm probability and the greatest performance improvement.","PeriodicalId":263114,"journal":{"name":"2023 3rd International Conference on Neural Networks, Information and Communication Engineering (NNICE)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121955894","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

An optimization high-resolution network for human pose recognition based on attention mechanism 基于注意机制的人体姿态识别高分辨率优化网络

2023 3rd International Conference on Neural Networks, Information and Communication Engineering (NNICE) Pub Date : 2023-02-24 DOI: 10.1109/NNICE58320.2023.10105762

Yu Feng, Junhua Zhou, Jinlong Yang, Yong Tang

引用次数: 0

Partial VGG16: reformed network for classification under partial occlusion Partial VGG16:改良后的局部闭塞分类网络

2023 3rd International Conference on Neural Networks, Information and Communication Engineering (NNICE) Pub Date : 2023-02-24 DOI: 10.1109/NNICE58320.2023.10105689

Bohang Sun, Bo Chen, Yuandan Deng

引用次数: 0

2023 3rd International Conference on Neural Networks, Information and Communication Engineering 2023第三届神经网络、信息与通信工程国际学术会议

2023 3rd International Conference on Neural Networks, Information and Communication Engineering (NNICE) Pub Date : 2023-02-24 DOI: 10.1109/nnice58320.2023.10105712

引用次数: 0

A Decentralized Data Crowdsourcing Framework: A Accountability and Confidentiality Perspective 一个分散的数据众包框架:问责制和保密性的视角

2023 3rd International Conference on Neural Networks, Information and Communication Engineering (NNICE) Pub Date : 2023-02-24 DOI: 10.1109/NNICE58320.2023.10105667

Yunzhou Wu, Xiangqian Dong

引用次数: 0