2022 International Symposium on Intelligent Signal Processing and Communication Systems (ISPACS)最新文献

Underwater Corrosion Recognition using Colour Illumination Mapping 基于彩色照明映射的水下腐蚀识别

2022 International Symposium on Intelligent Signal Processing and Communication Systems (ISPACS) Pub Date : 2022-11-22 DOI: 10.1109/ISPACS57703.2022.10082825

Amalina Ibrahim, W. Mohd-Isa, M. M. Su’ud, Shahbe Mat Desa

引用次数: 0

TransUNet for Cross-Domain Semantic Segmentation of Urban Scenery 基于TransUNet的城市景观跨域语义分割

2022 International Symposium on Intelligent Signal Processing and Communication Systems (ISPACS) Pub Date : 2022-11-22 DOI: 10.1109/ISPACS57703.2022.10082854

Wei Yuen Teh, I. K. T. Tan

引用次数: 0

Soft Information Adjustor for Four-Head/Two-Track (4H/2T) Bit-Patterned Magnetic Recording 用于四磁头/双轨(4H/2T)位图案磁记录的软信息调节器

2022 International Symposium on Intelligent Signal Processing and Communication Systems (ISPACS) Pub Date : 2022-11-22 DOI: 10.1109/ISPACS57703.2022.10082849

N. Rueangnetr, C. Warisarn, S. Koonkarnkhai, P. Kovintavewat

引用次数: 0

Enhancing The Linearity Range of LVDT Using Hyperbolic Sine Function 利用双曲正弦函数增强LVDT的线性范围

2022 International Symposium on Intelligent Signal Processing and Communication Systems (ISPACS) Pub Date : 2022-11-22 DOI: 10.1109/ISPACS57703.2022.10082839

P. Thongdit, K. Angkeaw

引用次数: 0

A deep learning based framework for badminton rally outcome prediction 基于深度学习的羽毛球比赛结果预测框架

2022 International Symposium on Intelligent Signal Processing and Communication Systems (ISPACS) Pub Date : 2022-11-22 DOI: 10.1109/ISPACS57703.2022.10082764

Yongwen Tan, John See, J. Abdullah, L. Wang, Kar-Weng Ban

引用次数: 2

Soft Information Scheme Based Multilayer Perceptron in Coded Bit-Patterned Media Recording System 基于软信息方案的多层感知器在编码位模式媒体记录系统中的应用

2022 International Symposium on Intelligent Signal Processing and Communication Systems (ISPACS) Pub Date : 2022-11-22 DOI: 10.1109/ISPACS57703.2022.10082799

J. Praiwan, C. Buajong, M. Mattayakan, C. Warisarn, S. Koonkarnkhai, P. Kovintavewat

{"title":"Soft Information Scheme Based Multilayer Perceptron in Coded Bit-Patterned Media Recording System","authors":"J. Praiwan, C. Buajong, M. Mattayakan, C. Warisarn, S. Koonkarnkhai, P. Kovintavewat","doi":"10.1109/ISPACS57703.2022.10082799","DOIUrl":"https://doi.org/10.1109/ISPACS57703.2022.10082799","url":null,"abstract":"In order to increase the efficiency of the recording system, both the inter-symbol interference (ISI) and inter-track interference (ITI) effects that impede the increase of an areal density (AD) in an ultra-high magnetic recording system, such as a bit-patterned media recording (BPMR) system, must be addressed. To improve the soft information or log-likelihood ratios (LLRs) obtained from the soft-output Viterbi algorithm (SOVA), we propose to use a multilayer perceptron (MLP), where three different patterns of the obtained soft information are employed as input data of MLP neural network in the training process under the coded recording system, while the recorded bit data sequences are fixed as a target data bit sequence. When compared to magnetic recording systems based on the partial response maximum likelihood (PRML) technique in both one and two-dimensional signal processing systems, the proposed recording system performs better in terms of bit error rate (BER), according to the results of computer simulation experiments.","PeriodicalId":410603,"journal":{"name":"2022 International Symposium on Intelligent Signal Processing and Communication Systems (ISPACS)","volume":"145 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132809855","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

Crowd Monitoring of Hajj Pilgrimage using Video Analytics and Deep Learning * 使用视频分析和深度学习的朝觐人群监测*

2022 International Symposium on Intelligent Signal Processing and Communication Systems (ISPACS) Pub Date : 2022-11-22 DOI: 10.1109/ISPACS57703.2022.10082848

Roman Bhuiyan, J. Abdullah, N. Hashim, Fahmid Al Farid

{"title":"Crowd Monitoring of Hajj Pilgrimage using Video Analytics and Deep Learning *","authors":"Roman Bhuiyan, J. Abdullah, N. Hashim, Fahmid Al Farid","doi":"10.1109/ISPACS57703.2022.10082848","DOIUrl":"https://doi.org/10.1109/ISPACS57703.2022.10082848","url":null,"abstract":"This paper presents developments in crowd analysis, with a specific emphasis on crowd density during the Hajj and Umrah pilgrimages. In recent years, there has been a rising interest in increasing video analytics and video surveillance to enhance the safety and security of pilgrims throughout their stay in Mecca. Crowd surveillance research and development are still in their infancy. Real-time monitoring of crowds is impeded by a lack of distinct crowd scenes or the high intensity of the crowd, which reduces its use. This paper proposed a fully convolutional neural network (FCNN) method for large crowd analysis, and it is able to classify the three classes of crowd density. This is intended to overcome existing technical challenges in video analysis in situations involving the circulation of a large number of pilgrims at a density of seven to eight per square meter. This endeavor intends to build a new dataset based on the Hajj scenario, in part to overcome the aforementioned difficulty. Manual and semi-automatic approaches are now used for video analysis, notably during Hajj. However, it is vital to automatically monitor pilgrim crowd events. Integrating FCNN classification with FCNN regression requires a strategy that is more powerful than the direct approach. Using ResNet50 and Fully Convolutional Neural Networks, a deep learning architecture is constructed to predict the density of certain crowd footage (FCNNs). The new dataset (Hajj-Crowd dataset) and using the recommended strategy, our solution obtained 100 % accuracy in crowd analysis, exceeding the state-of-the-art technology. In addition, the ResNet50 method achieved an accuracy of 98.6% for the developed crowd dataset.","PeriodicalId":410603,"journal":{"name":"2022 International Symposium on Intelligent Signal Processing and Communication Systems (ISPACS)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132169255","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

Vision of IoT, 5G and 6G Data Processing: Applications in Climate Change Mitigation 物联网、5G和6G数据处理的愿景:在减缓气候变化中的应用

2022 International Symposium on Intelligent Signal Processing and Communication Systems (ISPACS) Pub Date : 2022-11-22 DOI: 10.1109/ISPACS57703.2022.10082846

Soukaina El Maachi, Rachid Saadane, M. Wahbi, A. Chehri, Abdelmounaim Badaoui

引用次数: 1

Towards More Stable LIME For Explainable AI 为可解释的AI创造更稳定的LIME

2022 International Symposium on Intelligent Signal Processing and Communication Systems (ISPACS) Pub Date : 2022-11-22 DOI: 10.1109/ISPACS57703.2022.10082810

Ng Chung Hou, Hussain Sadiq Abuwala, C. H. Lim

{"title":"Towards More Stable LIME For Explainable AI","authors":"Ng Chung Hou, Hussain Sadiq Abuwala, C. H. Lim","doi":"10.1109/ISPACS57703.2022.10082810","DOIUrl":"https://doi.org/10.1109/ISPACS57703.2022.10082810","url":null,"abstract":"Although AI's development is remarkable, end users do not know how the AI has come to a specific conclusion due to the black-box nature of AI algorithms like deep learning. This has given rise to the field of explainable AI (XAI) where techniques are being developed to explain AI algorithms. One such technique is called Local Interpretable Model-Agnostic Explanations (LIME). LIME is popular because it is modelagnostic and works well with text, tabular and image data. While it has some good features, there are still room for improvements towards the original LIME algorithm especially it's stability. In this work, the LIME stability is being reviewed and three different approaches were investigated for its effectiveness in stability improvement which are; 1) using high sample size for stable ordering, 2) using an averaging method to reduce region flipping; and 3) to evaluate different super-pixels segmentation algorithms in generating stable LIME outcome. The experiment results shows a definite increase in the stability of the improved LIME compared to the baseline LIME and thus the reliability of using it practically.","PeriodicalId":410603,"journal":{"name":"2022 International Symposium on Intelligent Signal Processing and Communication Systems (ISPACS)","volume":"113 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124361244","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

Multiple Levels Perceptual Noise Backed Visual Information Fidelity for Picture Quality Assessment 多层感知噪声支持的图像质量评估视觉信息保真度

2022 International Symposium on Intelligent Signal Processing and Communication Systems (ISPACS) Pub Date : 2022-11-22 DOI: 10.1109/ISPACS57703.2022.10082853

Chenchen Peng, Mixia Wu, Kaiyuan Liu

引用次数: 2