Journal of Advanced Computational Intelligence and Intelligent Informatics最新文献_第10页

3D Street Object Detection from Monocular Images Using Deep Learning and Depth Information 利用深度学习和深度信息从单目图像中检测3D街道目标

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Journal of Advanced Computational Intelligence and Intelligent Informatics Pub Date : 2023-03-20 DOI: 10.20965/jaciii.2023.p0198

Wei Liu, Zhang Tao, Yun Ma, Longsheng Wei

引用次数: 0

Positioning Method of Four-Wheel-Steering Mobile Robots Based on Improved UMBmark of Michigan Benchmark Algorithm 基于改进的密歇根基准算法的四轮转向移动机器人定位方法

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Journal of Advanced Computational Intelligence and Intelligent Informatics Pub Date : 2023-03-20 DOI: 10.20965/jaciii.2023.p0135

Dianjun Wang, Meng Xu, Ya Chen, Haoxiang Zhong, Y. Zhu, Zilong Wang, Linlin Gao

引用次数: 0

Effect of Alcohol Consumption on the Frequency of Microsaccades 饮酒对微跳频的影响

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Journal of Advanced Computational Intelligence and Intelligent Informatics Pub Date : 2023-03-20 DOI: 10.20965/jaciii.2023.p0148

Toumi Ohara, Fumiya Kinoshita

引用次数: 0

Capsule Network Extension Based on Metric Learning 基于度量学习的胶囊网络扩展

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Journal of Advanced Computational Intelligence and Intelligent Informatics Pub Date : 2023-03-20 DOI: 10.20965/jaciii.2023.p0173

Nozomu Ohta, Shin Kawai, H. Nobuhara

{"title":"Capsule Network Extension Based on Metric Learning","authors":"Nozomu Ohta, Shin Kawai, H. Nobuhara","doi":"10.20965/jaciii.2023.p0173","DOIUrl":"https://doi.org/10.20965/jaciii.2023.p0173","url":null,"abstract":"A capsule network (CapsNet) is a deep learning model for image classification that provides robustness to changes in the poses of objects in the images. A capsule is a vector whose direction represents the presence, position, size, and pose of an object. However, with CapsNet, the distribution of capsules is concentrated in a class, and the number of capsules increases with the number of classes. In addition, learning is computationally expensive for a CapsNet. We proposed a method to increase the diversity of capsule directions and decrease the computational cost of CapsNet training by allowing a single capsule to represent multiple object classes. To determine the distance between classes, we used an additive angular margin loss called ArcFace. To validate the proposed method, the distribution of the capsules was determined using principal component analysis to validate the proposed method. In addition, using the MNIST, fashion-MNIST, EMNIST, SVHN, and CIFAR-10 datasets, as well as the corresponding affine-transformed datasets, we determined the accuracy and training time of the proposed method and original CapsNet. The accuracy of the proposed method improved by 8.91% on the CIFAR-10 dataset, and the training time reduced by more than 19% for each dataset compared with those of the original CapsNets.","PeriodicalId":45921,"journal":{"name":"Journal of Advanced Computational Intelligence and Intelligent Informatics","volume":"269 1","pages":"173-181"},"PeriodicalIF":0.7,"publicationDate":"2023-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78743763","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

Research on Image Inpainting Algorithms Based on Attention Guidance 基于注意力引导的图像绘制算法研究

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Journal of Advanced Computational Intelligence and Intelligent Informatics Pub Date : 2023-03-20 DOI: 10.20965/jaciii.2023.p0190

Yankun Shen, Yaya Su, L. Wang, Dongli Jia

{"title":"Research on Image Inpainting Algorithms Based on Attention Guidance","authors":"Yankun Shen, Yaya Su, L. Wang, Dongli Jia","doi":"10.20965/jaciii.2023.p0190","DOIUrl":"https://doi.org/10.20965/jaciii.2023.p0190","url":null,"abstract":"In recent years, the use of deep learning in image inpainting has yielded positive results. However, existing image inpainting algorithms do not pay sufficient attention to the structural and textural features of the image when inpainting, which leads to issues in the inpainting results such as blurring and distortion. To solve the above problems, a channel attention mechanism was introduced to emphasize the importance of structure and texture after extraction by the convolutional network. A bidirectional gated feature fusion module was employed to exchange and fuse the structural and textural features, ensuring the overall consistency of the image. In addition, the features of the image were better captured by selecting a deformable convolution that can adapt the receptive field to replace the ordinary convolution in the contextual feature aggregation module. This resulted in highly vivid and realistic restoration results with more reasonable details. The experiments showed that, compared with the current mainstream network, the repair results of this algorithm were more realistic, and the superiority of this algorithm was proved by qualitative and quantitative experiments.","PeriodicalId":45921,"journal":{"name":"Journal of Advanced Computational Intelligence and Intelligent Informatics","volume":"18 1","pages":"190-197"},"PeriodicalIF":0.7,"publicationDate":"2023-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91052634","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

optIFnet: A Capacitive Antenna Dipole Indention-Flexure Predictive Model Optimized Using Hybrid Lichtenberg Algorithm and Neural Network 基于Lichtenberg算法和神经网络优化的电容天线偶极子压痕-挠曲预测模型

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Journal of Advanced Computational Intelligence and Intelligent Informatics Pub Date : 2023-01-20 DOI: 10.20965/jaciii.2023.p0027

Mike Louie C. Enriquez, Ronnie S. Concepcion, R. Relano, Kate G. Francisco, Jonah Jahara G. Baun, Adrian Genevie G. Janairo, R. Baldovino, R. R. Vicerra, A. Bandala, E. Dadios

{"title":"optIFnet: A Capacitive Antenna Dipole Indention-Flexure Predictive Model Optimized Using Hybrid Lichtenberg Algorithm and Neural Network","authors":"Mike Louie C. Enriquez, Ronnie S. Concepcion, R. Relano, Kate G. Francisco, Jonah Jahara G. Baun, Adrian Genevie G. Janairo, R. Baldovino, R. R. Vicerra, A. Bandala, E. Dadios","doi":"10.20965/jaciii.2023.p0027","DOIUrl":"https://doi.org/10.20965/jaciii.2023.p0027","url":null,"abstract":"In performing underground imaging surveying, applying a coating in the antenna dipole plates with robust and durable material to stay protected against rough road features is vital to consider. By doing this, the mechanical properties of the metallic antenna dipole can be improved and be shielded from deterioration. With that, this study has developed an indentation-flexure algorithm optimized using a hybrid Lichtenberg algorithm (LA) and artificial neural network (ANN) that can predict the indentation-flexure as a function of the coating material’s elastic modulus, Poisson ratio, and thickness as well as the load antenna weight. Acrylic, epoxy, nylon 101, high-density polyethylene, and polyvinyl chloride were chosen as the top five most popular coating materials. A 120° titanium cone indenter with a 0.5-inch-diameter, slightly rounded point, and a constant compressive force of 200 N in the center was employed to plot and use a nonlinear mechanical finite element analysis on an antenna dipole plate using SolidWorks. Nature-inspired and evolutionary metaheuristics such as African vultures, Lichtenberg, and gorilla troop optimization algorithm including genetic algorithm (GA) were employed as optimized models for the hardness indentation for capacitively coupled antenna dipoles. Based on the results, the hybrid LA-ANN solution with a hidden neurons of 3000 and a sigmoid activation function is the best performing model as it acquired a MSE score of 0.0061 in validation and 0.1478 in testing compare to the other model with 0.1610 for GA with 100 hidden neurons with sigmoid activation function. Thus, LA-ANN model is considered as the optIFnet as it exhibited the best prediction performance and fastest convergence among all optimizers used.","PeriodicalId":45921,"journal":{"name":"Journal of Advanced Computational Intelligence and Intelligent Informatics","volume":"3 1","pages":"27-34"},"PeriodicalIF":0.7,"publicationDate":"2023-01-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79281931","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

Speech-Section Extraction Using Lip Movement and Voice Information in Japanese 基于唇动和语音信息的日语语段提取

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Journal of Advanced Computational Intelligence and Intelligent Informatics Pub Date : 2023-01-20 DOI: 10.20965/jaciii.2023.p0054

Etsuro Nakamura, Y. Kageyama, Satoshi Hirose

{"title":"Speech-Section Extraction Using Lip Movement and Voice Information in Japanese","authors":"Etsuro Nakamura, Y. Kageyama, Satoshi Hirose","doi":"10.20965/jaciii.2023.p0054","DOIUrl":"https://doi.org/10.20965/jaciii.2023.p0054","url":null,"abstract":"In recent years, several Japanese companies have attempted to improve the efficiency of their meetings, which has been a significant challenge. For instance, voice recognition technology is used to considerably improve meeting minutes creation. In an automatic minutes-creating system, identifying the speaker to add speaker information to the text would substantially improve the overall efficiency of the process. Therefore, a few companies and research groups have proposed speaker estimation methods; however, it includes challenges, such as requiring advance preparation, special equipment, and multiple microphones. These problems can be solved by using speech sections that are extracted from lip movements and voice information. When a person speaks, voice and lip movements occur simultaneously. Therefore, the speaker’s speech section can be extracted from videos by using lip movement and voice information. However, when this speech section contains only voice information, the voiceprint information of each meeting participant is required for speaker identification. When using lip movements, the speech section and speaker position can be extracted without the voiceprint information. Therefore, in this study, we propose a speech-section extraction method that uses image and voice information in Japanese for speaker identification. The proposed method consists of three processes: i) the extraction of speech frames using lip movements, ii) the extraction of speech frames using voices, and iii) the classification of speech sections using these extraction results. We used video data to evaluate the functionality of the method. Further, the proposed method was compared with state-of-the-art techniques. The average F-measure of the proposed method is determined to be higher than that of the conventional methods that are based on state-of-the-art techniques. The evaluation results showed that the proposed method achieves state-of-the-art performance using a simpler process compared to the conventional method.","PeriodicalId":45921,"journal":{"name":"Journal of Advanced Computational Intelligence and Intelligent Informatics","volume":"1 1","pages":"54-63"},"PeriodicalIF":0.7,"publicationDate":"2023-01-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89687225","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

Gradient-Based Scheduler for Scientific Workflows in Cloud Computing 基于梯度的云计算科学工作流调度器

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Journal of Advanced Computational Intelligence and Intelligent Informatics Pub Date : 2023-01-20 DOI: 10.20965/jaciii.2023.p0064

Danjing Wang, Huifang Li, Youwei Zhang, Baihai Zhang

引用次数: 0

SpeedX: Smart Speed Controller Model of Towed Subterranean Imaging System for Resistivity Data Distortion Reduction Using Computational Intelligence 利用计算智能降低电阻率数据失真的拖曳式地下成像系统的智能速度控制器模型

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Journal of Advanced Computational Intelligence and Intelligent Informatics Pub Date : 2023-01-20 DOI: 10.20965/jaciii.2023.p0003

R. Relano, Kate G. Francisco, Ronnie S. Concepcion, Mike Louie C. Enriquez, Jonah Jahara G. Baun, Adrian Genevie G. Janairo, R. R. Vicerra, A. Bandala, E. Dadios

{"title":"SpeedX: Smart Speed Controller Model of Towed Subterranean Imaging System for Resistivity Data Distortion Reduction Using Computational Intelligence","authors":"R. Relano, Kate G. Francisco, Ronnie S. Concepcion, Mike Louie C. Enriquez, Jonah Jahara G. Baun, Adrian Genevie G. Janairo, R. R. Vicerra, A. Bandala, E. Dadios","doi":"10.20965/jaciii.2023.p0003","DOIUrl":"https://doi.org/10.20965/jaciii.2023.p0003","url":null,"abstract":"Land surveying has been one of the core operations in performing underground imaging. It is known that dynamic and continuous resistivity readings were employed through this technique using the array of capacitive electrodes being towed with a light vehicle. However, the main challenge in doing subsurface surveying is the change in speed of the system when there are inevitable obstacles and sloping road surfaces. To address it, this study will develop prediction models using different computational intelligence such as multigene symbolic regression genetic programming (MSRGP), regression-based decision tree (RTree), and feed forward neural network (FFNN) that will result in a smart speed controller system that can maintain the constant speed of the towed subterranean system. The best performing prediction model will be considered as the SpeedX. The expected output is a correction factor that will signal the speed controller in slow down or inclined plane road environment to maintain a constant speed of 1.6667 m/s for avoidance of data distortion on land surveying. Thus, the MSEs for MSRGP, FFNN, and RTree are 0.00163, 0.00178, and 0.00240, respectively. This results in MSRGP as the best performing model and was considered as the SpeedX model. Other evaluation metrics were employed such as the MAE and R2 which signify the advantage of SpeedX. Furthermore, the comparison between the CI-controlled and uncontrolled towed subterranean imaging trailer system, as well as its advantages clearly highlight the advantage of embedded SpeedX in the system.","PeriodicalId":45921,"journal":{"name":"Journal of Advanced Computational Intelligence and Intelligent Informatics","volume":"36 1","pages":"3-11"},"PeriodicalIF":0.7,"publicationDate":"2023-01-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91164932","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

Digital Twin Concept Utilizing Electrical Resistivity Tomography for Monitoring Seawater Intrusion 利用电阻率层析成像技术监测海水入侵的数字孪生概念

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Journal of Advanced Computational Intelligence and Intelligent Informatics Pub Date : 2023-01-20 DOI: 10.20965/jaciii.2023.p0012

J. A. D. Leon, Ronnie S. Concepcion, R. Billones, Jonah Jahara G. Baun, Jose Miguel F. Custodio, R. R. Vicerra, A. Bandala, E. Dadios

引用次数: 0