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

筛选
英文 中文
Information-Based Rule Ranking for Associative Classification 基于信息的关联分类规则排序
H. Ong, Cheryl Yi Ming Neoh, Vhera Kaey Vijayaraj, Yi Xian Low
{"title":"Information-Based Rule Ranking for Associative Classification","authors":"H. Ong, Cheryl Yi Ming Neoh, Vhera Kaey Vijayaraj, Yi Xian Low","doi":"10.1109/ISPACS57703.2022.10082812","DOIUrl":"https://doi.org/10.1109/ISPACS57703.2022.10082812","url":null,"abstract":"Classification rule mining is a promising approach in data mining to create more interpretable and accurate prediction systems. This approach typically builds on top of well-known association rule mining and classification techniques, which identify a subset of rules known as class association rules (CAR), whose consequents are limited to target class labels. Existing classification rule mining methods have proven to provide better predictive accuracy while improving the interpretability and reasoning of a problem. Nevertheless, the challenges of such methods are mainly on a large number of generated CAR and the ranking and selection of interesting CAR for building classifiers. This paper proposed a hybrid of association rule mining (FP-growth) and neural network (sequential network of dense layers) techniques, focusing on using an information-based approach to rank and select interesting CAR. Preliminary experiments were conducted on nine UCI Machine Learning Repository datasets to examine the effect of the proposed hybrid model on generic datasets. The results show that the proposed approach achieved higher accuracy than other associative classification methods.","PeriodicalId":410603,"journal":{"name":"2022 International Symposium on Intelligent Signal Processing and Communication Systems (ISPACS)","volume":"59 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":"125127321","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
Heat Kernel Smoothing Using Node-Invariant, Node-Variant and Edge-Variant Graph Filters 使用节点不变、节点变和边变图滤波器的热核平滑
C. Tseng, Su-Ling Lee
{"title":"Heat Kernel Smoothing Using Node-Invariant, Node-Variant and Edge-Variant Graph Filters","authors":"C. Tseng, Su-Ling Lee","doi":"10.1109/ISPACS57703.2022.10082834","DOIUrl":"https://doi.org/10.1109/ISPACS57703.2022.10082834","url":null,"abstract":"In this paper, heat kernel smoothing (HKS) method is implemented by using polynomial graph filters. First, the discrete HKS is obtained from the heat equation by replacing continuous Laplacian operator with graph Laplacian matrix. The ideal transformation matrix of HKS is a matrix exponential which is only suitable for centralized implementation. Then, three distributed graph filters are presented to implement HKS including node-invariant graph filter, node-variant graph filter and edge-variant graph filter. The convex optimization method can be used to determine the optimal filter coefficients of these three kinds of graph filters. Next, these graph filters are compared in terms of design error, computational complexity and memory requirement. Finally, the effectiveness of HKS method is demonstrated by using temperature data denoising experiment of sensor network.","PeriodicalId":410603,"journal":{"name":"2022 International Symposium on Intelligent Signal Processing and Communication Systems (ISPACS)","volume":"74 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":"127671737","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
Three-Stage Salient Object Detection based on Integrated Priors 基于综合先验的三阶段显著目标检测
Yaqi Liu, Chao-gui Xia, Jianyi Zhang
{"title":"Three-Stage Salient Object Detection based on Integrated Priors","authors":"Yaqi Liu, Chao-gui Xia, Jianyi Zhang","doi":"10.1109/ISPACS57703.2022.10082817","DOIUrl":"https://doi.org/10.1109/ISPACS57703.2022.10082817","url":null,"abstract":"In this paper, a three-stage model is proposed for salient object detection. In the proposed method, an intuitive and straightforward pre-treatment method is firstly proposed to conduct superpixel segmentation adaptively, then superpixel-based graphs are constructed to express the structure of the image. To make full use of the information of individual images, multiple priors, including background prior, foreground prior, center prior and global contrast prior, are integrated in the three-stage detection model. In the first stage, under the assumption of background prior that the borders of the image are more likely to be the background, the absorbing Markov chain model is constructed to compute the saliency scores based on the absorbed time of each node in random walk. Then in the second stage, the saliency scores computed in the first stage, are taken as the foreground prior to compute the saliency scores via manifold ranking. In the third stage, center-biased global contrast filter combining center prior and global contrast prior is formulated to refine the saliency map. Experimental results demonstrate the effectiveness of the proposed three-stage method.","PeriodicalId":410603,"journal":{"name":"2022 International Symposium on Intelligent Signal Processing and Communication Systems (ISPACS)","volume":"1 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":"122355237","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
Sparse Method Towards Temporal Action Detection 面向时间动作检测的稀疏方法
Lijuan Wang, Suguo Zhu, Wuteng Qi, Jin Yang
{"title":"Sparse Method Towards Temporal Action Detection","authors":"Lijuan Wang, Suguo Zhu, Wuteng Qi, Jin Yang","doi":"10.1109/ISPACS57703.2022.10082820","DOIUrl":"https://doi.org/10.1109/ISPACS57703.2022.10082820","url":null,"abstract":"Temporal action detection aims to correctly predict the categories and temporal intervals of actions in an untrimmed video by using only video-level labels, which is a basic but challenging task in video understanding. Inspired by the work of Sparse R-CNN object detection, we present a purely sparse method in temporal action detection. In our method, a fixed sparse set of learnable temporal proposals, total length of $mathbf{N}$ (e.g.50), are provided to dynamic action interaction head to perform classification and localization. Sparse temporal action detection method completely avoids all efforts related to temporal candidates design and many- to-one label assignment. More importantly, final predictions are directly output without non-maximum suppression post-procedure. Extensive experiments show that our method achieves state-of-the-art performance for both action proposal and localization on THUMOS14 detection benchmark and competitive performance on ActivityNet-l.3challenge.","PeriodicalId":410603,"journal":{"name":"2022 International Symposium on Intelligent Signal Processing and Communication Systems (ISPACS)","volume":"38 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":"133276022","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
Deep Learning-Based Demodulation of Radio Signal 基于深度学习的无线电信号解调
K. Chia, Vishnu Monn Baskaran
{"title":"Deep Learning-Based Demodulation of Radio Signal","authors":"K. Chia, Vishnu Monn Baskaran","doi":"10.1109/ISPACS57703.2022.10082826","DOIUrl":"https://doi.org/10.1109/ISPACS57703.2022.10082826","url":null,"abstract":"M-ary quadrature amplitude modulation (M-QAM) modulated signal is commonly used in digital telecommunication systems for its arbitrarily high spectral efficiencies limited only by the noise level and linearity of the communications channel. Typical demodulation techniques for M-QAM signal utilize variants of coherent demodulation. This paper aims to exploit the robustness of deep learning, specifically by using neural networks to demodulate M-QAM symbols. This is achieved with simulated time-domain baseband M-QAM signals across a range of channel impairments namely additive white Gaussian noise, DC offset and I/Q imbalance. The presented results show an improvement when utilizing deep learning over optimal receiver.","PeriodicalId":410603,"journal":{"name":"2022 International Symposium on Intelligent Signal Processing and Communication Systems (ISPACS)","volume":"35 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":"127788632","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
Cross-View Integration for Stereoscopic Video Deblurring 立体视频去模糊的交叉视图集成
H. Imani, Md Baharul Islam
{"title":"Cross-View Integration for Stereoscopic Video Deblurring","authors":"H. Imani, Md Baharul Islam","doi":"10.1109/ISPACS57703.2022.10082850","DOIUrl":"https://doi.org/10.1109/ISPACS57703.2022.10082850","url":null,"abstract":"Stereoscopic cameras are now often seen in modern technology, including new Cellphones. Numerous elements, such as blur artifacts from camera/object motion, might influence the stereo video's quality. There are various deblurring techniques for monocular content, yet there are not many works for stereo content. A novel encoder-decoder-based stereoscopic video deblurring model presented in this work considers the subsequent left and right video frames. This approach employs the cross-view stereoscopic information to aid in deblurring. The proposed model uses the left and right stereoscopic frames and some nearby left and right frames as inputs to deblur the middle stereo frames. To extract their features, we first apply the stereo batch of frames to the encoder of our model. The left and right features are then fused together after being aggregated using the Parallax Attention Module (PAM). The decoder then extracts the deblurred stereo video frames using the output of PAM features. According to experimental findings on the recently proposed Stereo Blur dataset, the proposed approach effectively deblurs the stereoscopic video frames.","PeriodicalId":410603,"journal":{"name":"2022 International Symposium on Intelligent Signal Processing and Communication Systems (ISPACS)","volume":"7 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":"121615743","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 Consideration of High-Convergence Adaptive Deconvolution with Noise Reduction Function Based on Total Least Squares 基于总最小二乘的高收敛自适应降噪反卷积算法
Ryusuke Kono, Minoru Komatsu, H. Matsumoto
{"title":"A Consideration of High-Convergence Adaptive Deconvolution with Noise Reduction Function Based on Total Least Squares","authors":"Ryusuke Kono, Minoru Komatsu, H. Matsumoto","doi":"10.1109/ISPACS57703.2022.10082813","DOIUrl":"https://doi.org/10.1109/ISPACS57703.2022.10082813","url":null,"abstract":"In baseband transmission systems, if received signals do not include noises, we can accurately perform blind deconvolution for regenerating the transmitted signals. However, if the received signals include noises, the deconvolution performance generally deteriorates. In order to solve this problem, the re-generation method for transmitted signals based on Total Least Squares (TLS) with a noise reduction unit has been proposed. However, convergence rates of the method are low because it uses the gradient method. Therefore, in this paper, we propose a higher adaptive regeneration method for convergence using a recursive approach. This is because the convergence rate is expected to be higher this way. The proposed method was compared with the conventional method by computer simulation. As a result, we found that the proposed method can achieve higher convergence rate, maintaining high deconvolution performance.","PeriodicalId":410603,"journal":{"name":"2022 International Symposium on Intelligent Signal Processing and Communication Systems (ISPACS)","volume":"23 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":"122144137","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
Successive Interference Cancellation for Ultra-Dense 5G Heterogeneous Network 超密集5G异构网络的逐次干扰消除
Faizan Qamar, Syed Hussain Ali Kazmi, Rosilah Hassan, M. N. Hindia
{"title":"Successive Interference Cancellation for Ultra-Dense 5G Heterogeneous Network","authors":"Faizan Qamar, Syed Hussain Ali Kazmi, Rosilah Hassan, M. N. Hindia","doi":"10.1109/ISPACS57703.2022.10082829","DOIUrl":"https://doi.org/10.1109/ISPACS57703.2022.10082829","url":null,"abstract":"Interference Cancellation (IC) is an emerging technique for interference mitigation and network performance enhancement. Successive Interference Cancellation (SIC) has prominence among existing IC Techniques due to architectural similarity with traditional hardware for reduced cost effects. Moreover, SIC supports the transition to Fifth Generation (5G) heterogeneous networks environment due to flexible hardware compatibility. Therefore, in this study, we cover a detailed analysis of SIC in a multi-tier heterogeneous network through the system and channel-level mathematical modeling. Moreover, we simulated the heterogenous network environment to evaluate SIC success probability based on the number of users and Signal-to-interference-plus-Noise Ratio (SINR). Our results depict SIC as a potential promising IC solution for a heterogenous network.","PeriodicalId":410603,"journal":{"name":"2022 International Symposium on Intelligent Signal Processing and Communication Systems (ISPACS)","volume":"6 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":"130461378","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
No-Reference DIBR-Synthesized Video Quality Assessment based on Spatio-Temporal Texture Inconsistency Measurement 基于时空纹理不一致性测量的无参考dibr合成视频质量评估
Guangcheng Wang, Kezheng Sun, Lijuan Tang
{"title":"No-Reference DIBR-Synthesized Video Quality Assessment based on Spatio-Temporal Texture Inconsistency Measurement","authors":"Guangcheng Wang, Kezheng Sun, Lijuan Tang","doi":"10.1109/ISPACS57703.2022.10082823","DOIUrl":"https://doi.org/10.1109/ISPACS57703.2022.10082823","url":null,"abstract":"The relevant applications of depth-image-based-rendering (DIBR) exist mainly in the form of video sequences. However, existing studies on the quality assessment of DIBR-synthesized views primarily focused on DIBR-synthesized images. To this end, this paper proposes a DIBR-synthesized video quality evaluation metric based on measuring spatio-temporal texture inconsistency, dubbed STTI. Specifically, STTI first extracts the texture map of each frame in the spatial domain. Then, STTI further employs the histogram of oriented optical flow to extract the dynamic variations of adjacent frames' texture information in the spatio-temporal domain. Finally, STTI calculates the cosine similarity of the histograms of oriented optical flow between the texture maps of adjacent frames to measure spatio-temporal texture inconsistency. Experimental results on the publicly available datasets show that the proposed STTI outperforms the popular image/video quality assessment methods developed for natural scene and DIBR-synthesized views.","PeriodicalId":410603,"journal":{"name":"2022 International Symposium on Intelligent Signal Processing and Communication Systems (ISPACS)","volume":"26 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":"133785266","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
Voltage-Mode Biquad Multifunction Filter Using VCIIs 使用vci的电压型双四多功能滤波器
Koson Pitaksuttayaprot, Somkid Ritnathikul, W. Jaikla
{"title":"Voltage-Mode Biquad Multifunction Filter Using VCIIs","authors":"Koson Pitaksuttayaprot, Somkid Ritnathikul, W. Jaikla","doi":"10.1109/ISPACS57703.2022.10082805","DOIUrl":"https://doi.org/10.1109/ISPACS57703.2022.10082805","url":null,"abstract":"This paper describes a three-input, single-output, second-order filter with five responses, low-pass, high-pass, band-pass, band-reject, and all-pass functions, based on second-generation voltage conveyor (VCII). Both the quality factor and the pole frequency can be adjusted orthogonally. The proposed circuit is comprised of three VIIs, two capacitors, and six resistors. To obtain five filtering responses, the input signal applied into the input voltage nodes does not have to be doubled for the filter. Each filtering biquad function can be chosen by digitally selecting the appropriate input signals to input nodes of the filter. The output voltage node of the proposed multifunction filter is low impedance. The PSPICE application was used to design and simulate the filter. The simulation results from PSPICE are presented to validate the functionality of the presented versatile biquad filter. The simulation results coincide with the theoretical prediction very well.","PeriodicalId":410603,"journal":{"name":"2022 International Symposium on Intelligent Signal Processing and Communication Systems (ISPACS)","volume":"16 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":"134015533","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
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
相关产品
×
本文献相关产品
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信