2020 International Conference on Electronics, Information, and Communication (ICEIC)最新文献_第3页

A Self-Timed Ring based TRNG with Feedback Structure for FPGA Implementation 基于自定时环的带反馈结构TRNG的FPGA实现

2020 International Conference on Electronics, Information, and Communication (ICEIC) Pub Date : 2020-01-01 DOI: 10.1109/ICEIC49074.2020.9051375

Jun-Yeong Choe, K. Shin

引用次数: 3

Small Object Detection in Aerial Imagery using RetinaNet with Anchor Optimization 基于锚点优化的retanet航空图像小目标检测

2020 International Conference on Electronics, Information, and Communication (ICEIC) Pub Date : 2020-01-01 DOI: 10.1109/ICEIC49074.2020.9051269

Mobeen Ahmad, Muhammad Abdullah, Dongil Han

{"title":"Small Object Detection in Aerial Imagery using RetinaNet with Anchor Optimization","authors":"Mobeen Ahmad, Muhammad Abdullah, Dongil Han","doi":"10.1109/ICEIC49074.2020.9051269","DOIUrl":"https://doi.org/10.1109/ICEIC49074.2020.9051269","url":null,"abstract":"Deep Learning has successfully solved many computer vision problems sometimes in conjunction with traditional computer vision methods and sometimes by replacing them. In this paper, we aim to solve the problem of object detection by employing different methods from deep learning as well as computer vision. Significant amount of work is done in the domain of generic object detection, where usually objects (foreground) cover majority of image space as compared to background. In this paper we will focus on detecting small objects which constitute a tiny area as compared to background such as aerial imagery where desired objects such as people, cars etc. tend to appear relatively small. Such images have an intrinsic imbalanced class problem because background samples dominate object samples. We propose to use an anchor optimization method which will help reduce unnecessary region proposals as well as it can generate customized anchors depending upon the dataset. It can be used in conjunction with any single stage object detection framework. Its empirically noted that this anchor optimization technique improves accuracy over baseline frameworks.","PeriodicalId":271345,"journal":{"name":"2020 International Conference on Electronics, Information, and Communication (ICEIC)","volume":"193 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122345929","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: 12

Approximate Hardware Techniques for Energy-Quality Scaling Across the System 全系统能量质量缩放的近似硬件技术

2020 International Conference on Electronics, Information, and Communication (ICEIC) Pub Date : 2020-01-01 DOI: 10.1109/ICEIC49074.2020.9051208

Younghyun Kim, Joshua San Miguel, Setareh Behroozi, Tianen Chen, Kyuin Lee, Yongwoo Lee, Jingjie Li, Di Wu

引用次数: 5

Monolithic integration of tunable aperture and lens for distance sensor 用于距离传感器的可调光圈和镜头的单片集成

2020 International Conference on Electronics, Information, and Communication (ICEIC) Pub Date : 2020-01-01 DOI: 10.1109/ICEIC49074.2020.9051387

Yumee Kim, K. Chun, I. Saad

引用次数: 0

A New Approach to Designing Type 3 Compensator for Voltage-Mode Controlled Buck Converter 压模控制降压变换器3型补偿器设计的新方法

2020 International Conference on Electronics, Information, and Communication (ICEIC) Pub Date : 2020-01-01 DOI: 10.1109/ICEIC49074.2020.9051273

Syam Kumar Pidaparthy, Donghyuk Kim, B. Choi

引用次数: 2

A Study on the ESD Protection Device LIGBT with Floating N+ Diffusion Region Using Stack Technology 基于堆叠技术的浮动N+扩散区ESD保护器件light的研究

2020 International Conference on Electronics, Information, and Communication (ICEIC) Pub Date : 2020-01-01 DOI: 10.1109/ICEIC49074.2020.9051054

Kyoung-Il Do, Byung-Suk Lee, Jeong-Ju Seo, Je-Wook Woo, Yong-Seo Koo

引用次数: 1

High Efficiency 1700V 4H-SiC UMOSFET with Local Floating Superjunction 高效率的1700V 4H-SiC UMOSFET，具有局部浮动超结

2020 International Conference on Electronics, Information, and Communication (ICEIC) Pub Date : 2020-01-01 DOI: 10.1109/ICEIC49074.2020.9051234

Jinyoung Goh, Kwangsoo Kim

引用次数: 2

Convolutional Neural Network-based Direction-of-Arrival Estimation using Stereo Microphones for Drone 基于卷积神经网络的无人机立体传声器到达方向估计

2020 International Conference on Electronics, Information, and Communication (ICEIC) Pub Date : 2020-01-01 DOI: 10.1109/ICEIC49074.2020.9051364

Jeonghwan Choi, Joon‐Hyuk Chang

引用次数: 6

Characterization of Time Evolving Graph Using State-Space Modelling and its Application in Alzheimer's Disease Detection 基于状态空间模型的时间演化图表征及其在阿尔茨海默病检测中的应用

2020 International Conference on Electronics, Information, and Communication (ICEIC) Pub Date : 2020-01-01 DOI: 10.1109/ICEIC49074.2020.9088928

Himanshu Padole, S. Joshi, T. Gandhi

{"title":"Characterization of Time Evolving Graph Using State-Space Modelling and its Application in Alzheimer's Disease Detection","authors":"Himanshu Padole, S. Joshi, T. Gandhi","doi":"10.1109/ICEIC49074.2020.9088928","DOIUrl":"https://doi.org/10.1109/ICEIC49074.2020.9088928","url":null,"abstract":"Methods based on graph theoretical analysis of brain imaging data have been widely applied to detect various brain diseases like Alzheimer's disease (AD), autism spectrum disorder etc. But most of the conventional graph based methods assume the stationarity of the graph signals involved, neglecting the time varying nature of the associated graph connectivity. Recent studies involving the dynamic brain connectivity network revealed the altered brain connectivity dynamics in the disease state, thus making it a potential biomarker for the disease detection. In this paper, we propose a novel approach to characterize the dynamics of the time varying graph using the state-space representation of the graph signal, wherein the dynamic brain connectivity is modelled as a state of the system while the input graph signal serves as an observation. The dynamics of the time varying graph connectivity is then characterized by the state transition matrix which is obtained using the Kalman filtering algorithm. To detect AD using the altered brain connectivity dynamics, the SVM classifier is first trained using the state transition matrices of the training subjects, which is then used to classify a test subject as a normal control or having a mild cognitive impairment, the early stage of AD . The efficacy of the proposed model is verified using the resting state fMRI data from the ADNI dataset, wherein the proposed model outperformed state-of-the-art AD detection methods, possibly due to its ability to effectively characterize the brain connectivity dynamics.","PeriodicalId":271345,"journal":{"name":"2020 International Conference on Electronics, Information, and Communication (ICEIC)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133777249","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 Low Power Integrate and Fire Neuron Circuit for Spiking Neural Network 一种用于脉冲神经网络的低功耗集成火神经元电路

2020 International Conference on Electronics, Information, and Communication (ICEIC) Pub Date : 2020-01-01 DOI: 10.1109/ICEIC49074.2020.9051292

Jong-Beom Seo, K. Min, D. Kim, D. Kim, H. Mo

引用次数: 1