2022 IEEE Ninth International Conference on Communications and Electronics (ICCE)最新文献_第7页

Enhanced Model of Long-Short Term Memory for Music Generation in Hardware 硬件中音乐生成的长短期记忆增强模型

2022 IEEE Ninth International Conference on Communications and Electronics (ICCE) Pub Date : 2022-07-27 DOI: 10.1109/ICCE55644.2022.9852030

Thinh Do Quang, Trang Hoang

{"title":"Enhanced Model of Long-Short Term Memory for Music Generation in Hardware","authors":"Thinh Do Quang, Trang Hoang","doi":"10.1109/ICCE55644.2022.9852030","DOIUrl":"https://doi.org/10.1109/ICCE55644.2022.9852030","url":null,"abstract":"Music generation becomes an economically important research field for the time being since the rapid growth of the entertainment industry. Among various methods for creating music, Long-Short Term Memory, or LSTM, is a preferable way for creating sequence of music notes while maintaining the harmony. This study proposes an enhanced LSTM model in hardware where the range of notes are also included in the generation process as a new factor. Data that comes in and out the LSTM are handled under normalization to reduce the range of note sequence, as well as to increase the consonance. Measurements were taken on the proposed LTSM, and another basic one, which were both implemented on hardware, to analyze the quality of the proposed LSTM and also the impact of the note range over the generation process. It appeared that the proposed LSTM could reach the harmony much efficiently based on the note range analysis; and achieve it faster than the basic LSTM since a smaller number of epoch was required. Those results indicate that LSTM can work with additional factor to improve its quality, rather than concentrating only on the data values.","PeriodicalId":388547,"journal":{"name":"2022 IEEE Ninth International Conference on Communications and Electronics (ICCE)","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124674907","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

Axial Attention MLP-Mixer: A New Architecture for Image Segmentation 轴向注意mlp -混频器:一种新的图像分割架构

2022 IEEE Ninth International Conference on Communications and Electronics (ICCE) Pub Date : 2022-07-27 DOI: 10.1109/ICCE55644.2022.9852066

Hong-Phuc Lai, Thi-Thao Tran, Van-Truong Pham

引用次数: 8

Investigation of phase compensation lens to improve the gain of Vivaldi antenna in Ka-band 相位补偿透镜提高ka波段维瓦尔第天线增益的研究

2022 IEEE Ninth International Conference on Communications and Electronics (ICCE) Pub Date : 2022-07-27 DOI: 10.1109/ICCE55644.2022.9852039

T. Dam, G. Houzet, T. Lacrevaz, Gwenaёl Gaborit, T. Vuong

引用次数: 0

On Optimal Channel Uses in Ultra-Reliable Short-Packet Relaying Communications 超可靠短包中继通信中最优信道使用研究

2022 IEEE Ninth International Conference on Communications and Electronics (ICCE) Pub Date : 2022-07-27 DOI: 10.1109/ICCE55644.2022.9852051

T. Chu, H. Zepernick, T. Duong

引用次数: 0

Common-Mode Voltage Reduction in Two-Level Voltage Source Inverter with Carrier-Based PWM Strategies 基于载波PWM策略的二电平电压源逆变器共模降压

2022 IEEE Ninth International Conference on Communications and Electronics (ICCE) Pub Date : 2022-07-27 DOI: 10.1109/ICCE55644.2022.9852084

Phong Nguyen Hong Le, Nho-Van Nguyen

引用次数: 1

Violence Detection using Feature Fusion of Optical Flow and 3D CNN on AICS-Violence Dataset 基于AICS-Violence数据集的光流与三维CNN特征融合的暴力检测

2022 IEEE Ninth International Conference on Communications and Electronics (ICCE) Pub Date : 2022-07-27 DOI: 10.1109/ICCE55644.2022.9852065

C. Vo-Le, Hung Sy Vo, Thien Duy Vu, Nguyen Hong Son

{"title":"Violence Detection using Feature Fusion of Optical Flow and 3D CNN on AICS-Violence Dataset","authors":"C. Vo-Le, Hung Sy Vo, Thien Duy Vu, Nguyen Hong Son","doi":"10.1109/ICCE55644.2022.9852065","DOIUrl":"https://doi.org/10.1109/ICCE55644.2022.9852065","url":null,"abstract":"In this paper, we introduce a new self-developed violence dataset named AICS-Violence. It contains 7576 high-resolution video clips of violent and non-violent scenarios collected by outdoor security cameras. It includes two different test sets with additional non-violent but seemingly violent actions as well. One of those test sets has data collected using a different camera angle compared to that of the training set and the remaining test set. To focus on each group of people in frames, we develop a method to automatically crop candidate boxes from detected human bounding boxes. Furthermore, two methods named 3D DenseNet Fusion OF RGB and 3D DenseNet Fusion OFnom RGB are proposed. In both methods, two 3D DenseNets are used to extract features from RGB and visualized optical flow respectively. Then, two different ways of fusion namely addition and normalization-based multiplication are applied to the two methods respectively. Evaluation results show that our methods achieve slightly better performance in the first test set and especially significantly better generation than those of some other state-of-the-art methods on the second test set.","PeriodicalId":388547,"journal":{"name":"2022 IEEE Ninth International Conference on Communications and Electronics (ICCE)","volume":"217 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124276977","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: 1

Protection Solution for an EH IoT Networks Under a Cooperative UAV Eavesdropper and Malicious Jammer Attack 无人机协同窃听和恶意干扰攻击下的EH物联网网络防护方案

2022 IEEE Ninth International Conference on Communications and Electronics (ICCE) Pub Date : 2022-07-27 DOI: 10.1109/ICCE55644.2022.9852028

Van Nhan Vo, Ha Le Vu, Nguyen Quoc Long, Hung Tran, Dang Viet-Hung, Cong Le, Tu Dac Ho

{"title":"Protection Solution for an EH IoT Networks Under a Cooperative UAV Eavesdropper and Malicious Jammer Attack","authors":"Van Nhan Vo, Ha Le Vu, Nguyen Quoc Long, Hung Tran, Dang Viet-Hung, Cong Le, Tu Dac Ho","doi":"10.1109/ICCE55644.2022.9852028","DOIUrl":"https://doi.org/10.1109/ICCE55644.2022.9852028","url":null,"abstract":"Secrecy and system performance are major concerns when implementing the Internet of Things (IoT) paradigm in fifth-generation (5G) communication networks. The detection capability and system performance of an energy harvesting (EH) Internet of Things (IoT) architecture are explored in the presence of an unmanned aerial vehicle (UAV) eavesdropper (UAV EAV). The communication protocol is divided into two phases as follows: 1) a friendly jammer detects the UAV EAV and the relays harvest energy from a power beacon (PB) in the first phase. 2) a ground base station (BS) sends a confidential signal to relays; the selected relay then uses its harvested energy to forward this confidential signal to IoT destinations (IDs) using the decode-and-forward (DF) technique. Simultaneously, the friendly jammer generates an artificial signal to counteract the detected UAV EAV in the second phase. In this Word, a closed-form expression for the probability of detecting the UAV EAV is derived to analyze the detection performance. Furthermore, the leakage probability and outage probability of the considered IoT architecture are determined. Finally, Monte Carlo simulations are employed to verify our approach.","PeriodicalId":388547,"journal":{"name":"2022 IEEE Ninth International Conference on Communications and Electronics (ICCE)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133846874","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

Effective Authentication Mechanism for Vehicular Fog Infrastructure 车辆雾基础设施的有效认证机制

2022 IEEE Ninth International Conference on Communications and Electronics (ICCE) Pub Date : 2022-07-27 DOI: 10.1109/ICCE55644.2022.9852081

Ta Thi Kim Hue, Nguyen Gia Duoc Nguyen Duy Tuan, An Braeken, K. Steenhaut, Kieu-Ha Phung Seee

引用次数: 0

CNN quantization for anatomical landmarks classification from upper gastrointestinal endoscopic images on Edge Devices 边缘设备上上消化道内镜图像解剖标志分类的CNN量化

2022 IEEE Ninth International Conference on Communications and Electronics (ICCE) Pub Date : 2022-07-27 DOI: 10.1109/ICCE55644.2022.9852098

M. Le, Quang Tung Nguyen, V. Dao, Thanh-Hai Tran

{"title":"CNN quantization for anatomical landmarks classification from upper gastrointestinal endoscopic images on Edge Devices","authors":"M. Le, Quang Tung Nguyen, V. Dao, Thanh-Hai Tran","doi":"10.1109/ICCE55644.2022.9852098","DOIUrl":"https://doi.org/10.1109/ICCE55644.2022.9852098","url":null,"abstract":"In recent years, Artificial Intelligence (AI) has played an important role in our daily life. Especially convolutional neural network (CNN) in medical image analysis has been getting more and more attention recently. Using CNN on a portable medical device (such as edge devices) can give out a handy yet accurate disease diagnosis in the medical field. However, the CNNs require a high amount of computing resources which limit the use of CNNs on edge devices. By reducing the size of CNN models while keeping high accuracy, it is easier to integrate CNN onto an edge device for real-time uses. This paper investigates and compares two strategies for CNN quantization to reduce the number of resources required. The first two-stages strategy is based on post-training quantization where the CNN is firstly trained conventionally then post-quantized to achieve its lightweight version. The second one-stage strategy conducts the quantization directly during CNN model training. On the one hand, we discuss the main advantages as well as the drawbacks of each strategy. On the other hand, we implement a state-of-the-art CNN model (i.e. MobileNet-V2) and quantitatively evaluate the performance of the original model with two lightweight models produced by post-quantization and aware training quantization in terms of accuracy and memory requirement. Experiments, conducted on a dataset of endoscopic images for the task of anatomical landmarks classification, show the potential to deploy such techniques on edge devices.","PeriodicalId":388547,"journal":{"name":"2022 IEEE Ninth International Conference on Communications and Electronics (ICCE)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129690610","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

Development of DNN-based diagnostic platform for self-diagnosis of electric vehicle automatic transmission controller production equipment 基于dnn的电动汽车自动变速器控制器生产设备自诊断诊断平台的开发

2022 IEEE Ninth International Conference on Communications and Electronics (ICCE) Pub Date : 2022-07-27 DOI: 10.1109/ICCE55644.2022.9852022

R. Kim, S. Oh, J. Kim

引用次数: 0