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2023 IEEE International Conference on Acoustics, Speech, and Signal Processing Workshops (ICASSPW)最新文献

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A New Multiway MFDM Based Technique For EEG Source Localisation And Interpretation 一种新的基于多路MFDM的脑电信号源定位与解释技术
2023 IEEE International Conference on Acoustics, Speech, and Signal Processing Workshops (ICASSPW) Pub Date : 2023-06-04 DOI: 10.1109/ICASSPW59220.2023.10193324
Anchal Yadav, Monika Agrawal, S. Joshi
{"title":"A New Multiway MFDM Based Technique For EEG Source Localisation And Interpretation","authors":"Anchal Yadav, Monika Agrawal, S. Joshi","doi":"10.1109/ICASSPW59220.2023.10193324","DOIUrl":"https://doi.org/10.1109/ICASSPW59220.2023.10193324","url":null,"abstract":"The clinical applications of EEG Source Localization are seen in the analysis of epilepsy, schizophrenia, Parkinson, stress, and tumor. This paper proposes a novel brain source localization method using a multiway Multivariate Fourier Decomposition Method (MFDM) based technique. Firstly, a multiway array (tensor) is formed using MFDM, a novel way of forming a tensor from EEG signals. Then, this tensor is decomposed into various independent components using Canonical Polyadic Decomposition (CPD). Each independent component is used to reconstruct separate EEG signals corresponding to every independent source. Lastly, localization techniques like SPICE and LIKES are used to obtain the source locations. The results are compared with traditional methods like MNE, sLORETA, LASSO, and Space Time Frequency (STF) based tensor decomposition method. Further, real EEG signals during an arithmetic task are used to support and verify the proposed method in real application.","PeriodicalId":158726,"journal":{"name":"2023 IEEE International Conference on Acoustics, Speech, and Signal Processing Workshops (ICASSPW)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121793872","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
Representation Matters: The Case for Diversifying Sign Language Avatars 代表问题:多样化的手语化身的案例
2023 IEEE International Conference on Acoustics, Speech, and Signal Processing Workshops (ICASSPW) Pub Date : 2023-06-04 DOI: 10.1109/ICASSPW59220.2023.10193409
Maria Kopf, R. Omardeen, Davy Van Landuyt
{"title":"Representation Matters: The Case for Diversifying Sign Language Avatars","authors":"Maria Kopf, R. Omardeen, Davy Van Landuyt","doi":"10.1109/ICASSPW59220.2023.10193409","DOIUrl":"https://doi.org/10.1109/ICASSPW59220.2023.10193409","url":null,"abstract":"As interest in sign language machine translation grows, there is more focus on developing and refining avatar technology to present translation outputs. While signing avatar technology research has focused on legibility and appearance, there has been little attention paid to representing diversity in signing avatars, and the default is often a white female animation. We present data from focus groups conducted in two ongoing sign language machine translation projects in Europe that give insight into deaf end-users’ desires for diversity in avatar representations. Our results reveal a strong desire for full customisability, including options for representing diversity in gender expression and ethnicity, as well as accommodating sociolinguistic variation and personal identity through modified avatar signing styles. This work provides initial insights, but considerable future research is necessary, particularly with minorities and sub-groups within deaf communities.","PeriodicalId":158726,"journal":{"name":"2023 IEEE International Conference on Acoustics, Speech, and Signal Processing Workshops (ICASSPW)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125490091","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
Identification of Predictive Subnetwork for Brain Network-Based Psychiatric Diagnosis: An Information-Theoretic Perspective 基于脑网络的精神病诊断预测子网络的识别:信息论视角
2023 IEEE International Conference on Acoustics, Speech, and Signal Processing Workshops (ICASSPW) Pub Date : 2023-06-04 DOI: 10.1109/ICASSPW59220.2023.10193344
Kaizhong Zheng, Shujian Yu, Badong Chen
{"title":"Identification of Predictive Subnetwork for Brain Network-Based Psychiatric Diagnosis: An Information-Theoretic Perspective","authors":"Kaizhong Zheng, Shujian Yu, Badong Chen","doi":"10.1109/ICASSPW59220.2023.10193344","DOIUrl":"https://doi.org/10.1109/ICASSPW59220.2023.10193344","url":null,"abstract":"Graph neural networks (GNNs) have recently been applied to develop useful diagnostic tools for psychiatric disorders. However, due to the lack of interpretability, clinicians are hard to identify quantifiable and personalizable biomarkers which provide biologically and clinically relevance. We introduce three recently proposed GNN-based psychiatric disorders diagnostic models, namely BrainIB, Graph-PRI and CI-GNN, from an information-theoretic perspective. These models are able to discriminate psychiatric patients from healthy controls and identify predictive subgraph, a.k.a. biomarkers, solely from observations. We demonstrate their improved classification accuracy and interpretability on ABIDE database. We also put forward three proposals for future research.","PeriodicalId":158726,"journal":{"name":"2023 IEEE International Conference on Acoustics, Speech, and Signal Processing Workshops (ICASSPW)","volume":"52 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123131896","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
Model-Distributed Inference in Multi-Source Edge Networks 多源边缘网络中的模型分布式推理
2023 IEEE International Conference on Acoustics, Speech, and Signal Processing Workshops (ICASSPW) Pub Date : 2023-06-04 DOI: 10.1109/ICASSPW59220.2023.10193154
Pengzhen Li, H. Seferoglu, Erdem Koyuncu
{"title":"Model-Distributed Inference in Multi-Source Edge Networks","authors":"Pengzhen Li, H. Seferoglu, Erdem Koyuncu","doi":"10.1109/ICASSPW59220.2023.10193154","DOIUrl":"https://doi.org/10.1109/ICASSPW59220.2023.10193154","url":null,"abstract":"Distributed inference techniques can be broadly classified into data-distributed and model-distributed schemes. In data-distributed inference (DDI), each worker carries the entire deep neural network (DNN) model, but processes only a subset of the data. However, feeding the data to workers results in high communication costs especially when the data is large. An emerging paradigm is model-distributed inference (MDI), where each worker carries only a subset of DNN layers. In MDI, a source device that has data processes a few layers of DNN and sends the output to a neighboring device. This process ends when all layers are processed in a distributed manner. In this paper, we investigate MDI with multiple sources, i.e., when more than one device has data. We design a multisource MDI (MS-MDI), which optimizes task scheduling decisions across multiple source devices and workers. Experimental results on a real-life testbed of NVIDIA Jetson TX2 edge devices show that MS-MDI improves the inference time significantly as compared to baselines.","PeriodicalId":158726,"journal":{"name":"2023 IEEE International Conference on Acoustics, Speech, and Signal Processing Workshops (ICASSPW)","volume":"183 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115070425","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
Empiric Bayesian Inversion of Evaporation Ducts From Synthetic Phased-Array Data 基于合成相控阵数据的蒸发管道经验贝叶斯反演
2023 IEEE International Conference on Acoustics, Speech, and Signal Processing Workshops (ICASSPW) Pub Date : 2023-06-04 DOI: 10.1109/ICASSPW59220.2023.10193739
T. Rogers, P. Gerstoft
{"title":"Empiric Bayesian Inversion of Evaporation Ducts From Synthetic Phased-Array Data","authors":"T. Rogers, P. Gerstoft","doi":"10.1109/ICASSPW59220.2023.10193739","DOIUrl":"https://doi.org/10.1109/ICASSPW59220.2023.10193739","url":null,"abstract":"We perform inversions of low-altitude refractivity from phased-array observations of the electromagnetic (EM) field using empiric sampling. Populations of samples are used to represent the probability of observation for a given environmental state, with all states equally likely. A single phased-array observation is assumed. The posterior probability of an environmental state is based on the number of its members within the neighborhood of the observation relative to the total overall states that occur within the neighborhood. The results show the dependence of the posterior probability densities on both the environmental state itself and the state of sensing as signal-to-noise ratio.","PeriodicalId":158726,"journal":{"name":"2023 IEEE International Conference on Acoustics, Speech, and Signal Processing Workshops (ICASSPW)","volume":"111 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129951979","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 Clustered Federated Learning Approach for Estimating the Quality of Experience of Web Users 一种估计Web用户体验质量的聚类联邦学习方法
2023 IEEE International Conference on Acoustics, Speech, and Signal Processing Workshops (ICASSPW) Pub Date : 2023-06-04 DOI: 10.1109/ICASSPW59220.2023.10193530
Simone Porcu, Alessandro Floris, L. Atzori
{"title":"A Clustered Federated Learning Approach for Estimating the Quality of Experience of Web Users","authors":"Simone Porcu, Alessandro Floris, L. Atzori","doi":"10.1109/ICASSPW59220.2023.10193530","DOIUrl":"https://doi.org/10.1109/ICASSPW59220.2023.10193530","url":null,"abstract":"In this paper, we present FedCLWAvg, a novel clustered Federated Learning (FL) approach for estimating the Quality of Experience (QoE) of Web users. FedCLWAvg performs clustering on the weights of the trained local models (CLW stands for clustered weights) to identify users with similar data distribution. In the context of QoE modelling, the hypothesis is that personal differences (in terms of perceived QoE for the same stimuli) between groups of users are reflected in different weights of the trained local models. Then, each identified cluster learns its own model using the FedAvg algorithm. To validate our approach, we used the Web QoE dataset including the subjective quality of 3,400 Web browsing sessions identified by the measurement of 9 Web session features. Experimental results have shown that FedCLWAvg achieved greater QoE estimation performance than the classical FedAvg algorithm in terms of mean accuracy and recall, F1-score, and precision computed for the single quality scores.","PeriodicalId":158726,"journal":{"name":"2023 IEEE International Conference on Acoustics, Speech, and Signal Processing Workshops (ICASSPW)","volume":"245 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131253597","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
Sievenet: An Efficient Model Utilizing H.265 Codec Structure for Video Object Detection Sievenet:一种利用H.265编解码结构的高效视频目标检测模型
2023 IEEE International Conference on Acoustics, Speech, and Signal Processing Workshops (ICASSPW) Pub Date : 2023-06-04 DOI: 10.1109/ICASSPW59220.2023.10193722
O. Koyun, B. U. Töreyin
{"title":"Sievenet: An Efficient Model Utilizing H.265 Codec Structure for Video Object Detection","authors":"O. Koyun, B. U. Töreyin","doi":"10.1109/ICASSPW59220.2023.10193722","DOIUrl":"https://doi.org/10.1109/ICASSPW59220.2023.10193722","url":null,"abstract":"In the field of video content analysis, object detection is a crucial task. The High Efficient Video Coding (H.265, HEVC) standard’s coding structures are strongly correlated with the video content, creating an opportunity to utilize these structures for video object detection in a computationally efficient way. To address this, we present a video object detection method that partitions frames into macroblocks based on the H.265 structure. Blocks with spatially high-frequency content go through a dynamic-layer approach that subjects them to deeper analysis with more layers, while blocks with spatially low-frequency content undergo fewer layers to enable a lower computational load. Results on ImageNet-Vid Dataset indicate that our approach has the potential to save significant computational resources while maintaining accurate object detection performance.","PeriodicalId":158726,"journal":{"name":"2023 IEEE International Conference on Acoustics, Speech, and Signal Processing Workshops (ICASSPW)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134107364","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
Speeding up Detection and Imaging Using Quantum Radars 利用量子雷达加速探测和成像
2023 IEEE International Conference on Acoustics, Speech, and Signal Processing Workshops (ICASSPW) Pub Date : 2023-06-04 DOI: 10.1109/ICASSPW59220.2023.10193120
David Luong, B. Balaji, S. Rajan
{"title":"Speeding up Detection and Imaging Using Quantum Radars","authors":"David Luong, B. Balaji, S. Rajan","doi":"10.1109/ICASSPW59220.2023.10193120","DOIUrl":"https://doi.org/10.1109/ICASSPW59220.2023.10193120","url":null,"abstract":"In this paper, we provide a simple introduction to the enhancement achievable by quantum radars. We show that an important type of quantum radar, known as quantum two-mode squeezing (QTMS) radar, is mathematically connected to noise radars. The quantum advantage stems from QTMS radar’s ability to mitigate the effect of quantum noise, leading to greater contrast in the matched filter output between the target present and target absent cases. This reduced the integration time needed to detect a target. For imaging applications that rely on matched filtering, the quantum enhancement leads to a speedup in imaging as well.","PeriodicalId":158726,"journal":{"name":"2023 IEEE International Conference on Acoustics, Speech, and Signal Processing Workshops (ICASSPW)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130260108","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
Symbiotic Artificial Intelligence: Order Picking And Ambient Sensing 共生人工智能:秩序拾取与环境感知
2023 IEEE International Conference on Acoustics, Speech, and Signal Processing Workshops (ICASSPW) Pub Date : 2023-06-04 DOI: 10.1109/ICASSPW59220.2023.10193633
Zhe Ming Chng, Calix Tang, Darshan Krishnaswamy Haoyang Yang, Shivang Chopra, Jon Womack, Thad Starner
{"title":"Symbiotic Artificial Intelligence: Order Picking And Ambient Sensing","authors":"Zhe Ming Chng, Calix Tang, Darshan Krishnaswamy Haoyang Yang, Shivang Chopra, Jon Womack, Thad Starner","doi":"10.1109/ICASSPW59220.2023.10193633","DOIUrl":"https://doi.org/10.1109/ICASSPW59220.2023.10193633","url":null,"abstract":"Using egocentric video and head motion data from 67 order picking tasks (244 picks;149 orders), we learn visual models of the 10 objects picked to fulfill the orders. Boundary segmentations of the four actions (pick, carry, place, carry empty) of order picking had an average test RMSE of 1.11 seconds using computer vision and 5.53 seconds using only head motion $( approx 39.8$ seconds/task). The 10 objects were clustered with 93.8% accuracy using weak supervision provided by the picks (which could occur in any order) specified in the tasks. We apply the 10 resulting models on independent test data to recognize three objects involving 50 tasks (185 picks;98 orders) and 10 objects involving 10 tasks (35 picks;24 orders). Accuracy was up to 90.3% and 69.1%, respectively. We propose order picking as a practical use case of egocentric Symbiotic AI, where ambient sensing is used without explicit supervision to train an agent which can then help the user improve task speed and accuracy.1","PeriodicalId":158726,"journal":{"name":"2023 IEEE International Conference on Acoustics, Speech, and Signal Processing Workshops (ICASSPW)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114998378","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
ISAC From The Sky: Net-Zero Energy Uav Trajectory Design ISAC来自天空:净零能耗无人机轨迹设计
2023 IEEE International Conference on Acoustics, Speech, and Signal Processing Workshops (ICASSPW) Pub Date : 2023-06-04 DOI: 10.1109/ICASSPW59220.2023.10193205
Xiaoye Jing, Fan Liu, C. Masouros
{"title":"ISAC From The Sky: Net-Zero Energy Uav Trajectory Design","authors":"Xiaoye Jing, Fan Liu, C. Masouros","doi":"10.1109/ICASSPW59220.2023.10193205","DOIUrl":"https://doi.org/10.1109/ICASSPW59220.2023.10193205","url":null,"abstract":"Unmanned aerial vehicle (UAV) can work as a portable base station providing not only the communication service to ground users, but also the sensing functionality to localize targets of interests. In this paper, we consider a scenario with one rotary-wing UAV to transmit signals for a communication user and receive echoes for a target estimation. We propose a multi-stage trajectory design to jointly improve both the communication and sensing (C&S) performances. We formulate the trajectory design problem into a weighted optimization problem and propose an iterative algorithm to solve it. Numerical results show the performance trade-off between C&S.","PeriodicalId":158726,"journal":{"name":"2023 IEEE International Conference on Acoustics, Speech, and Signal Processing Workshops (ICASSPW)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114668016","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
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