2023 Sixth International Symposium on Computer, Consumer and Control (IS3C)最新文献_第3页

Early Alzheimer’s Disease Detection Through YOLO-Based Detection of Hippocampus Region in MRI Images 基于yolo的MRI图像海马区的早期阿尔茨海默病检测

2023 Sixth International Symposium on Computer, Consumer and Control (IS3C) Pub Date : 2023-06-01 DOI: 10.1109/IS3C57901.2023.00017

Junaidul Islam, Elvin Nur Furqon, Isack Farady, Chi-Wen Lung, Chih-Yang Lin

{"title":"Early Alzheimer’s Disease Detection Through YOLO-Based Detection of Hippocampus Region in MRI Images","authors":"Junaidul Islam, Elvin Nur Furqon, Isack Farady, Chi-Wen Lung, Chih-Yang Lin","doi":"10.1109/IS3C57901.2023.00017","DOIUrl":"https://doi.org/10.1109/IS3C57901.2023.00017","url":null,"abstract":"Magnetic Resonance Imaging (MRI) is currently one of the most promising tools for detecting Alzheimer’s disease (AD), as it allows for the analysis of brain regions affected by the disease, such as the hippocampus. However, the availability of labeled datasets for hippocampus regions in MRI images is limited, and manually annotating such images can be expensive and time-consuming task, particularly for large datasets. To overcome this challenge, we propose a deep learning approach that leverages object detection models to automatically identify the hippocampus region in MRI images. In our study, we employed various YOLO-based models to detect and classify the AD classes based on the hippocampus region in MRI images. We specifically selected the latest state-of-the-art YOLO variants, including YOLOv3, YOLOv4, YOLOv5, YOLOv6, and YOLOv7. Our approach shows potential for improving the early detection of Alzheimer’s disease using deep learning and object detection and may be useful for developing automated diagnostic tools for clinical applications. We conducted experiments in two scenarios to validate our proposed idea: one-class detection and two-class detection. One-class detection detects a specific class based on the appearance of the hippocampus region, while two-class detection aims to detect and classify the AD level based on the hippocampus. Our preliminary results demonstrate that YOLO variants are viable for accurately detecting the hippocampus region in MRI images, with potential applications in hippocampus detection.","PeriodicalId":142483,"journal":{"name":"2023 Sixth International Symposium on Computer, Consumer and Control (IS3C)","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130913016","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

Application of Virtual Synchronous Generator in Power Systems 虚拟同步发电机在电力系统中的应用

2023 Sixth International Symposium on Computer, Consumer and Control (IS3C) Pub Date : 2023-06-01 DOI: 10.1109/IS3C57901.2023.00076

Wen-Zhuang Jiang, C. Liao, Y. Hsu

引用次数: 0

High Step-Up Converter 高升压变换器

2023 Sixth International Symposium on Computer, Consumer and Control (IS3C) Pub Date : 2023-06-01 DOI: 10.1109/IS3C57901.2023.00078

K. Hwu, Pei-Ching Tseng

引用次数: 0

A Two-Stage Pipelined Algorithm for Recognition Tasks: Using License Plate Recognition as an Example 识别任务的两阶段流水线算法——以车牌识别为例

2023 Sixth International Symposium on Computer, Consumer and Control (IS3C) Pub Date : 2023-06-01 DOI: 10.1109/IS3C57901.2023.00014

Jia-Ming Yeh, Garnett Chang, Jason P Lee, Wei-Yang Lin

引用次数: 0

High-Resolution Art Painting Completion using Multi-Region Laplacian Fusion 使用多区域拉普拉斯融合的高分辨率艺术绘画完成

2023 Sixth International Symposium on Computer, Consumer and Control (IS3C) Pub Date : 2023-06-01 DOI: 10.1109/IS3C57901.2023.00016

Irawati Nurmala Sari, Kei Masaoka, Jun’Nosuke Takarabe, Weiwei Du

{"title":"High-Resolution Art Painting Completion using Multi-Region Laplacian Fusion","authors":"Irawati Nurmala Sari, Kei Masaoka, Jun’Nosuke Takarabe, Weiwei Du","doi":"10.1109/IS3C57901.2023.00016","DOIUrl":"https://doi.org/10.1109/IS3C57901.2023.00016","url":null,"abstract":"Image completion has made impressive advancements based on deep learning approaches. However, even with advanced deep learning such as Generative Adversarial Networks (GAN), the restored area is not always optimal due to small-scale texture synthesis in high resolution and inferring missing information about image content from distant contexts, resulting in distorted lines and unnatural colors, especially in art painting completion with complicated structures and textures. Although several precious art paintings have been well-preserved by curators in museums, some frequent damages such as scratches, torn-out areas, and holes are still visible and require challenging physical repairs. Therefore, for practical refinement, some researchers convert them into high-resolution digital paintings to generate crisp brush strokes, textures, shapes, and tones by assuming similarities with the original physical ones. Based on these observations, we propose proceeding with a high-resolution art painting completion by applying a superior traditional method, named Multi-Region Laplacian Fusion. We attempt to recover irregular missing regions expected as the damages of ordinary paintings that often occur. To address high-resolution inpainting, we integrate two completions using the Laplacian pyramid and patch-based propagation. We then apply Alpha blending among both results to yield the fused reaction completion. Our experiments firmly validate the effectiveness of our proposed method to complete art paintings with random irregular missing regions.","PeriodicalId":142483,"journal":{"name":"2023 Sixth International Symposium on Computer, Consumer and Control (IS3C)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128126429","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

Optimizing Weighted Permutation in Support Vector Machine for the Detection of Epilepsy via EEG Data Analysis 基于EEG数据分析的支持向量机加权排列优化癫痫检测

2023 Sixth International Symposium on Computer, Consumer and Control (IS3C) Pub Date : 2023-06-01 DOI: 10.1109/is3c57901.2023.00100

I. Wahyono, Shih-Chung Chen

{"title":"Optimizing Weighted Permutation in Support Vector Machine for the Detection of Epilepsy via EEG Data Analysis","authors":"I. Wahyono, Shih-Chung Chen","doi":"10.1109/is3c57901.2023.00100","DOIUrl":"https://doi.org/10.1109/is3c57901.2023.00100","url":null,"abstract":"Epileptic seizures can range from short periods to violent shaking over long periods. Epilepsy is a disease that tends to occur repeatedly and cannot be cured. However, the occurrence of epileptic seizures can be controlled through medication. This study tried to detect epilepsy features via electroencephalogram (EEG) data analysis. The EEG data is divided into several windows using segmentation or decomposition. EEG Data will be extracted from each window using a modified Weighted Permutation Entropy (WPE) to produce one feature per window where the number of features of each EEG data will equal the number of windows obtained in the EEG data recording process. This research used k-fold cross-validation by dividing the data into training and testing data, classified using a Support Vector Machine. The EEG database used in this study came from Temple University Hospital EEG (TUH EEG), obtained online with as much as 1500 data. This EEG database consists of epileptic seizures (set 1) and non-epileptic seizures (sets 2, 3, 4, 5), each with 300 data. Based on testing, using this method produces an average accuracy of 81.29%.","PeriodicalId":142483,"journal":{"name":"2023 Sixth International Symposium on Computer, Consumer and Control (IS3C)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125108388","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

Analyzing the 3D Image Characteristics for a Pile of Hex Nuts using the Depth from Focus Method 用聚焦深度法分析一堆六角螺母的三维图像特征

2023 Sixth International Symposium on Computer, Consumer and Control (IS3C) Pub Date : 2023-06-01 DOI: 10.1109/IS3C57901.2023.00065

Sheng-Cong You, Cheng-Yu Peng

引用次数: 0

Interpretation of Transplanted Positions Based on Image Super-Resolution Approaches for Rice Paddies 基于图像超分辨率方法的水稻移植位置解译

2023 Sixth International Symposium on Computer, Consumer and Control (IS3C) Pub Date : 2023-06-01 DOI: 10.1109/is3c57901.2023.00102

You-Cheng Chen, Yih-Shyh Chiou, Mu-Jan Shih

引用次数: 0

A Pilot Study of Applying Machine Learning to Adjust the Content Generation and Personalization in Developing a Virtual Reality Hand Grip Strength Exergame Prototype 在虚拟现实握力游戏原型开发中应用机器学习调整内容生成和个性化的试点研究

2023 Sixth International Symposium on Computer, Consumer and Control (IS3C) Pub Date : 2023-06-01 DOI: 10.1109/IS3C57901.2023.00037

Pai-Hsun Chen, Yin-Nan Wang, Lu-Han Chen

引用次数: 0

Application of Genetic Algorithm to Path Planning Problem of Automatic Navigation Parking Spaces in Parking Lots 遗传算法在停车场自动导航车位路径规划中的应用

2023 Sixth International Symposium on Computer, Consumer and Control (IS3C) Pub Date : 2023-06-01 DOI: 10.1109/IS3C57901.2023.00040

Yu-Huei Cheng, Cheng-Yao Kang

{"title":"Application of Genetic Algorithm to Path Planning Problem of Automatic Navigation Parking Spaces in Parking Lots","authors":"Yu-Huei Cheng, Cheng-Yao Kang","doi":"10.1109/IS3C57901.2023.00040","DOIUrl":"https://doi.org/10.1109/IS3C57901.2023.00040","url":null,"abstract":"With the accelerated process of urbanization, traffic congestion and parking difficulties have gradually become key factors affecting the quality of life of urban residents. To address this challenge, this study proposes an intelligent parking lot navigation and optimal parking spot path planning method based on genetic algorithm. This method fully utilizes the superior adaptability of genetic algorithm, can flexibly adapt to changes in the parking lot environment, search for the optimal parking spot, thereby shortening the distance of vehicle driving in the parking lot, reducing traffic congestion, and saving time for finding parking spots. In this study, we first constructed a comprehensive parking lot model, including parking spaces, occupied parking spaces, entrances and exits, and other relevant parameters. Next, we designed and implemented a genetic algorithm, including individual generation, fitness function, crossover operation, mutation operation, and genetic optimization process. To demonstrate the practicality of the algorithm, we used a Tkinter graphical user interface to simulate the parking lot environment and present the path planning results. After experimental verification, the proposed intelligent parking lot navigation and optimal parking spot path planning method based on genetic algorithm in this study performed well in the driving performance of the parking lot, effectively solving the problem of parking difficulties and improving the efficiency of urban traffic operation.","PeriodicalId":142483,"journal":{"name":"2023 Sixth International Symposium on Computer, Consumer and Control (IS3C)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123735314","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