TENCON 2021 - 2021 IEEE Region 10 Conference (TENCON)最新文献_第6页

Classification of Breast Cancer using User-Defined Weighted Ensemble Voting Scheme 基于用户自定义加权集合投票方案的乳腺癌分类

TENCON 2021 - 2021 IEEE Region 10 Conference (TENCON) Pub Date : 2021-12-07 DOI: 10.1109/TENCON54134.2021.9707374

Ajay Kumar, R. Sushil, A. Tiwari

引用次数: 1

A Blockchain-Based Security Scheme for Vehicular Ad Hoc Networks in Smart Cities 智慧城市中基于区块链的车辆自组织网络安全方案

TENCON 2021 - 2021 IEEE Region 10 Conference (TENCON) Pub Date : 2021-12-07 DOI: 10.1109/TENCON54134.2021.9707356

X. Li, M. Ma, Yong Xing Yong

引用次数: 1

Resource-Conscious High-Performance Models for 2D-to-3D Single-View Reconstruction 面向2d到3d单视图重建的资源意识高性能模型

TENCON 2021 - 2021 IEEE Region 10 Conference (TENCON) Pub Date : 2021-12-07 DOI: 10.1109/TENCON54134.2021.9707193

Suraj Bidnur, Dhruv Srikanth, Sanjeev Gurugopinath

引用次数: 0

Insect Detection and Identification using YOLO Algorithms on Soybean Crop 基于YOLO算法的大豆作物昆虫检测与鉴定

TENCON 2021 - 2021 IEEE Region 10 Conference (TENCON) Pub Date : 2021-12-07 DOI: 10.1109/TENCON54134.2021.9707354

Shani Verma, S. Tripathi, Anurag Singh, Muneendra Ojha, R. Saxena

引用次数: 9

Speaker Localization in Smartphones using Adaptive Eigenvalue Decomposition with Noise Reduction 基于自适应特征值分解和降噪的智能手机说话人定位

TENCON 2021 - 2021 IEEE Region 10 Conference (TENCON) Pub Date : 2021-12-07 DOI: 10.1109/TENCON54134.2021.9707231

J. M. Mendoza, Franz A. de Leon

{"title":"Speaker Localization in Smartphones using Adaptive Eigenvalue Decomposition with Noise Reduction","authors":"J. M. Mendoza, Franz A. de Leon","doi":"10.1109/TENCON54134.2021.9707231","DOIUrl":"https://doi.org/10.1109/TENCON54134.2021.9707231","url":null,"abstract":"Most smartphones are dual microphone devices capable of determining the direction of arrival of an utterance from a speaker source. The widespread use of such devices helps in improving hearing aid systems without increased expenses. These types of sound source localization (SSL) systems with two sensors take advantage of time delay estimation (TDE) techniques such as cross-correlation and adaptive eigenvalue decomposition (AED). The former lacks reliability in situations with reverb, while the latter suffers from background noise. In this paper, we observed the effect of integrating a noise reduction algorithm to AED for SSL applications. Given the robustness of AED with room reverb, we expect performance improvement of TDE from noise-reduced outputs. The minimum mean-square error with decision-directed (MMSE-DD) noise estimation algorithm acts as a filter for the received signals. We proposed $text{MMSE}-text{DD}+text{AED}$ to obtain an SSL algorithm in poor environment conditions. The empirical results of the system yielded 69.87%, which is a significant improvement from previous SSL algorithms in smartphones. Furthermore, a tilt compensation solution boosted the accuracy to 79.28%, addressing the dynamic behavior of the built-in microphones of the device.","PeriodicalId":405859,"journal":{"name":"TENCON 2021 - 2021 IEEE Region 10 Conference (TENCON)","volume":"99 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131523542","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

Convolutional Neural Network or Vision Transformer? Benchmarking Various Machine Learning Models for Distracted Driver Detection 卷积神经网络还是视觉变压器?对分心驾驶员检测的各种机器学习模型进行基准测试

TENCON 2021 - 2021 IEEE Region 10 Conference (TENCON) Pub Date : 2021-12-07 DOI: 10.1109/TENCON54134.2021.9707341

Hong Vin Koay, Joon Huang Chuah, C. Chow

{"title":"Convolutional Neural Network or Vision Transformer? Benchmarking Various Machine Learning Models for Distracted Driver Detection","authors":"Hong Vin Koay, Joon Huang Chuah, C. Chow","doi":"10.1109/TENCON54134.2021.9707341","DOIUrl":"https://doi.org/10.1109/TENCON54134.2021.9707341","url":null,"abstract":"Driver distraction is the main factor of severe traffic accidents and has become an essential issue in the traffic safety field. Hence, driver inattention systems are crucial in ensuring the safety of road users. With the introduction of Vision Transformer for computer vision tasks, there is a lack of comprehensive evaluation of various models for distracted driver detection. Hence, we raise the question - does vision transformers outperform convolutional neural networks (CNNs) in the field of detecting driving distraction? In this work, we evaluate and perform in-depth evaluations of various state-of-the-art CNN and Vision Transformer models to detect the distracted driver. We believe this will aid future researchers in this field in benchmarking their novel models with state-of-the-art models. We select ResNet, VGGNet, DenseNet, and EfficientNet as the candidates for CNN, while ViT, Swin Transformer, DeiT, and CaiT for Vision Transformer. We perform our benchmark on the American University of Cairo Distracted Driving Dataset (AUC-DDD) which consists of ten distracted classes. It is observed that CNN should be considered first if the downstream task is specific and the available dataset is small. An in-depth discussion and analysis are included in this work.","PeriodicalId":405859,"journal":{"name":"TENCON 2021 - 2021 IEEE Region 10 Conference (TENCON)","volume":"27 3","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133008405","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: 4

Modelling the thermal effects of tumbling on CubeSats equipped with HTS coils 模拟装有高温超导线圈的立方体卫星翻滚时的热效应

TENCON 2021 - 2021 IEEE Region 10 Conference (TENCON) Pub Date : 2021-12-07 DOI: 10.1109/TENCON54134.2021.9707304

T. Berry, J. R. Olatunji, Chris Acheson

{"title":"Modelling the thermal effects of tumbling on CubeSats equipped with HTS coils","authors":"T. Berry, J. R. Olatunji, Chris Acheson","doi":"10.1109/TENCON54134.2021.9707304","DOIUrl":"https://doi.org/10.1109/TENCON54134.2021.9707304","url":null,"abstract":"High-temperature superconductivity (HTS) has potential to be useful for space applications, with HTS devices being capable of generating very high magnetic fields in compact devices. Use of HTS in space and integration into small satellites requires careful consideration of the solar power availability and thermal management to maintain a cryogenic environment. This paper uses a modelling approach to investigate the power and thermal implications for an HTS magnet and cryocooler inside a 3U CubeSat which is tumbling uncontrollably in a 500 km circular orbit. We show that, under the assumptions of the model, attitude control is necessary to reach and maintain a cryogenic environment for the HTS magnet. As CubeSats are power starved due to their limited surface area for solar panels, even a slight net angular velocity approximately halves the power availability for the cryocooler to counteract the significant number of radiation sources in a low-Earth orbit. As such, this paper highlights the need for attitude control to achieve HTS in space. Additionally, we investigate scenarios which could cause a satellite to tumble, and discuss the possibility of using the interaction between the HTS magnet and Earth's magnetic field to de-tumble a satellite which has lost its attitude control.","PeriodicalId":405859,"journal":{"name":"TENCON 2021 - 2021 IEEE Region 10 Conference (TENCON)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133489453","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 Comparison of Electromagnetic Behaviour in Classical and Mutually Coupled Switched Reluctance Generators 经典和互耦合开关磁阻发生器的电磁特性比较

TENCON 2021 - 2021 IEEE Region 10 Conference (TENCON) Pub Date : 2021-12-07 DOI: 10.1109/TENCON54134.2021.9707462

M. Heidarian, Adam P. R. Taylor, Tim Anderson

引用次数: 0

Ambisonics and Sonic Simulation in Virtual Reality 虚拟现实中的立体声和声音模拟

TENCON 2021 - 2021 IEEE Region 10 Conference (TENCON) Pub Date : 2021-12-07 DOI: 10.1109/TENCON54134.2021.9707299

Yulia Yagunova, M. Poletti, Paul D. Teal

{"title":"Ambisonics and Sonic Simulation in Virtual Reality","authors":"Yulia Yagunova, M. Poletti, Paul D. Teal","doi":"10.1109/TENCON54134.2021.9707299","DOIUrl":"https://doi.org/10.1109/TENCON54134.2021.9707299","url":null,"abstract":"It can be challenging for opera singers to access their performance venues for rehearsal due to venue sched-ules or travel restrictions. Virtual reality (VR) or augmented reality (AR) technologies provide the possibility for rehearsal in a virtual venue. However, these technologies are mainly focused on visuals, rather than on the sonic plausibility of a virtual space. Moreover, existing self-auralization methods have one or more of the following limitations: a small choice of virtual venues, restricted user movement, generic rather than individualized configuration, and an expensive rehearsal space. This paper presents an Ambisonics method that addresses these limitations. The method simulates the acoustics of a chosen performance venue in real-time, by simulating oral-binaural room impulse responses (OBRIRs). This method allows changing the virtual venue and user-related data, and provides three-degrees-of-freedom (3DoF) for user head movement. The method is validated using quantitative and qualitative methods, and challenges of future real-time implementation are discussed. Despite the challenges, the method is capable of facilitating virtual rehearsal in real-time while providing for greater user flexibility.","PeriodicalId":405859,"journal":{"name":"TENCON 2021 - 2021 IEEE Region 10 Conference (TENCON)","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128431676","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

The Role of Face Embeddings in Classification of Personality Traits from Portrait Images 人脸嵌入在人格特征分类中的作用

TENCON 2021 - 2021 IEEE Region 10 Conference (TENCON) Pub Date : 2021-12-07 DOI: 10.1109/TENCON54134.2021.9707263

SREEVIDYA P, S. Veni, V. R. M. Oruganti

引用次数: 0