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2021 5th IEEE International Conference on Cybernetics (CYBCONF)最新文献

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A Feasibility Study on Hand Gesture Recognition in Natural Conversation 自然会话中手势识别的可行性研究
2021 5th IEEE International Conference on Cybernetics (CYBCONF) Pub Date : 2021-06-08 DOI: 10.1109/CYBCONF51991.2021.9464141
Dian Christy Silpani, Keishi Suematsu, Kaori Yoshida
{"title":"A Feasibility Study on Hand Gesture Recognition in Natural Conversation","authors":"Dian Christy Silpani, Keishi Suematsu, Kaori Yoshida","doi":"10.1109/CYBCONF51991.2021.9464141","DOIUrl":"https://doi.org/10.1109/CYBCONF51991.2021.9464141","url":null,"abstract":"This paper proposes to approach natural hand gestures that occur in natural conversations. Hand gesture recognition in Human-Robot Interaction is considered a preliminary study for the next step, based on the vision system of a humanoid robot. We experimented as a feasibility study on hand gestures recognition in natural conversation. The conversations between an experimental assistant (the first author) and two different subjects (both female) were recorded in the experiment. Each conversation includes two people, one of whom is the subject of the hand gesture detection that appears during the conversation. We manually captured the hand gestures that appear naturally during the session and analyzed their duration and frequency of occurrence from each video. As a result of conversations with two subjects, it was clear that hand gestures significantly impact people’s conversations. We observed that hand gestures with the same word or similar meaning appeared several times with the same intention, such as pointing at something and emphasizing a sentence or word. The topic of natural hand-gesture recognition by a robot will be a challenge. Cultural diversity makes the scope of natural hand-gesture broad, but this can be considered a topic in developing the knowledge of human-robot interaction in the future.","PeriodicalId":231194,"journal":{"name":"2021 5th IEEE International Conference on Cybernetics (CYBCONF)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124784720","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
Welcome Message from Honorary and General Chairs 名誉主席及总会主席致欢迎辞
2021 5th IEEE International Conference on Cybernetics (CYBCONF) Pub Date : 2021-06-08 DOI: 10.1109/cybconf51991.2021.9464130
{"title":"Welcome Message from Honorary and General Chairs","authors":"","doi":"10.1109/cybconf51991.2021.9464130","DOIUrl":"https://doi.org/10.1109/cybconf51991.2021.9464130","url":null,"abstract":"","PeriodicalId":231194,"journal":{"name":"2021 5th IEEE International Conference on Cybernetics (CYBCONF)","volume":"300 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122981069","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
Towards Learning Hierarchical Structures with SyncMap 用SyncMap学习层次结构
2021 5th IEEE International Conference on Cybernetics (CYBCONF) Pub Date : 2021-06-08 DOI: 10.1109/CYBCONF51991.2021.9464145
Tham Yik Foong, Danilo Vasconcellos Vargas
{"title":"Towards Learning Hierarchical Structures with SyncMap","authors":"Tham Yik Foong, Danilo Vasconcellos Vargas","doi":"10.1109/CYBCONF51991.2021.9464145","DOIUrl":"https://doi.org/10.1109/CYBCONF51991.2021.9464145","url":null,"abstract":"Objects or events perceived by human are often organized in a sequence that forms into chunks which exhibit hierarchical structure, e.g., words or videos. Such a sequence can be represented as a group of temporally correlated variables at multiple levels referred as chunk. In this work, an unsupervised method known as SyncMap is used to perform chunking on sequences of input data with hierarchical structure. We design a fixed and probabilistic chunk experiment to test our model capability, measured by the mutual information between the predicted chunk with the ground truth. Surprisingly, without too much modification on the original algorithm, the result has shown that SyncMap can perform chunking with hierarchical structure, although with limitation. Possible future works are proposed to overcome the limitation. Observation on the dynamic of weight map also indicates that SyncMap adapts to the low-level hierarchical representation of chunks faster than the one on the higher level.","PeriodicalId":231194,"journal":{"name":"2021 5th IEEE International Conference on Cybernetics (CYBCONF)","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132024872","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
Acquiring Consensus Solutions by Multi-human-agent-based Evolutionary Computation 基于多人类智能体进化计算的共识解获取
2021 5th IEEE International Conference on Cybernetics (CYBCONF) Pub Date : 2021-06-08 DOI: 10.1109/CYBCONF51991.2021.9464147
Hironao Sakamoto, Koutaro Nakamoto, K. Ohnishi
{"title":"Acquiring Consensus Solutions by Multi-human-agent-based Evolutionary Computation","authors":"Hironao Sakamoto, Koutaro Nakamoto, K. Ohnishi","doi":"10.1109/CYBCONF51991.2021.9464147","DOIUrl":"https://doi.org/10.1109/CYBCONF51991.2021.9464147","url":null,"abstract":"The paper proposes a system to acquire consensus solutions among people to a multiobjective problem which does not require direct communication among the people. It relies on multi-human-agent-based evolutionary computation (Mhab-EC) with a mechanism for making solutions of agents converged. In the system, people prepare their own agents who can be tuned by themselves, and then submit their agents to a simulation of Mhab-EC and acquire a convergence solution from the simulation. Then, examining the simulation result, they tune their agents again to be closer to their desired solutions and submit the agents to the simulation and obtain a convergence solution. The mechanism repeats this procedure pre-determined times and outputs a convergence solution of the final simulation as the consensus solution. In basic evaluation of the system, we focus on if the system can make solution converged and show that it can indeed do it.","PeriodicalId":231194,"journal":{"name":"2021 5th IEEE International Conference on Cybernetics (CYBCONF)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130704562","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
Estimating the Effect of COVID-19 Contact Tracing Application Using Agent-Based Simulation 基于agent的COVID-19接触者追踪应用效果评估
2021 5th IEEE International Conference on Cybernetics (CYBCONF) Pub Date : 2021-06-08 DOI: 10.1109/CYBCONF51991.2021.9464149
T. Murata, Kanta Yamashita
{"title":"Estimating the Effect of COVID-19 Contact Tracing Application Using Agent-Based Simulation","authors":"T. Murata, Kanta Yamashita","doi":"10.1109/CYBCONF51991.2021.9464149","DOIUrl":"https://doi.org/10.1109/CYBCONF51991.2021.9464149","url":null,"abstract":"In this paper, we estimate the effectiveness of COVID-19 contact tracing applications using agent-based simulations. We develop a simulation model and see how many infected patients can be reduced using the applications. In order to investigate the effectiveness of the applications, we enlarge the tracing area from direct contacts to indirect contacts. The results of our agent-based simulation show that detecting indirect contacts can reduce the number of infected patients.","PeriodicalId":231194,"journal":{"name":"2021 5th IEEE International Conference on Cybernetics (CYBCONF)","volume":"113 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124742329","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: 3
Forecasting Potential Sales of Bread Products at Stores by Network Embedding 基于网络嵌入的面包产品销售预测
2021 5th IEEE International Conference on Cybernetics (CYBCONF) Pub Date : 2021-06-08 DOI: 10.1109/CYBCONF51991.2021.9464142
Kohei Takahashi, Yusuke Goto
{"title":"Forecasting Potential Sales of Bread Products at Stores by Network Embedding","authors":"Kohei Takahashi, Yusuke Goto","doi":"10.1109/CYBCONF51991.2021.9464142","DOIUrl":"https://doi.org/10.1109/CYBCONF51991.2021.9464142","url":null,"abstract":"In this work, we study the forecast of the potential sales of out-of-stock products in retail stores using factory shipment data. A precise prediction of the potential sales of out-of-stock products in retail stores is beneficial for both baking factories and retail stores because it optimizes the supply chain by introducing a new product in proper quantity at retail stores, and it also creates new opportunities for baking factories to sell their products to retail stores. This study uses high-dimensional and sparse baking factory shipment data, which are unsuitable for prediction using conventional methods because the data have a high computation time and missing values. We employ a network embedding method, LINE, to derive similar stores based on their sales and predict their potential sales. We confirmed that our proposed method outperforms a simple prediction method (Baseline) and t-SNE for accurate product sales prediction via simulation experiments. We also verified our proposed method’s applicability when the forecasting target is expanded to products sold in fewer stores and with lower volume.","PeriodicalId":231194,"journal":{"name":"2021 5th IEEE International Conference on Cybernetics (CYBCONF)","volume":"214 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122377923","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 CNN Approximation Method Based on Low-bit Quantization and Random Forests 基于低比特量化和随机森林的CNN逼近方法
2021 5th IEEE International Conference on Cybernetics (CYBCONF) Pub Date : 2021-06-08 DOI: 10.1109/CYBCONF51991.2021.9464152
Shota Yatabe, Sora Isobe, Yoichi Tomioka, H. Saito, Y. Kohira, Qiangfu Zhao
{"title":"A CNN Approximation Method Based on Low-bit Quantization and Random Forests","authors":"Shota Yatabe, Sora Isobe, Yoichi Tomioka, H. Saito, Y. Kohira, Qiangfu Zhao","doi":"10.1109/CYBCONF51991.2021.9464152","DOIUrl":"https://doi.org/10.1109/CYBCONF51991.2021.9464152","url":null,"abstract":"In recent years, the use of image recognition technology in edge devices has been increasing. To achieve low-power and low-latency inference of convolutional neural networks (CNNs) in edge devices, methods that reduce the number of operations, such as pruning, have been actively researched. However, even after applying these existing methods, we still need to calculate many multiply-accumulate (MAC) operations. In this paper, we propose a hardware-friendly CNN approximation method based on low-bit quantization and random forests to reduce the number of operations and operation cost of CNN inference. In our experiments, we reduce the number of operations by 30.8% for LeNet and by 27.1% for ResNet18 while maintaining high image classification accuracy.","PeriodicalId":231194,"journal":{"name":"2021 5th IEEE International Conference on Cybernetics (CYBCONF)","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133101949","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
Stabilization of the Modular Selective Neural Network Model Based on Inter-Class Correlation 基于类间相关的模块化选择神经网络模型的镇定
2021 5th IEEE International Conference on Cybernetics (CYBCONF) Pub Date : 2021-06-08 DOI: 10.1109/CYBCONF51991.2021.9464136
I. M. Chowdhury, Kai Su, Huitao Wang, Qiangfu Zhao
{"title":"Stabilization of the Modular Selective Neural Network Model Based on Inter-Class Correlation","authors":"I. M. Chowdhury, Kai Su, Huitao Wang, Qiangfu Zhao","doi":"10.1109/CYBCONF51991.2021.9464136","DOIUrl":"https://doi.org/10.1109/CYBCONF51991.2021.9464136","url":null,"abstract":"We propose an optimization of Modular Selective Network or MS-Net by reducing the number of expert network evaluations. MS-Net is composed of a router and a set of expert networks. In our original proposal, MS-Net is constructed based on a Round-Robin dataset partition with controlled redundancy among the subsets of classes. In this paper, we propose a novel way for reducing the inference cost by performing Inter-Class-Correlation (ICC) analysis through calculating the joint-probability of appearance of top-2 classes in router’s prediction. Next, we construct subset of classes on the most frequently occurring class pairs and train experts on those subsets. We do not enforce redundancy in these subsets, thus during inference, only one expert is leveraged per sample. Our empirical results show that, with the ResNet-20 backbone, the optimized MS-Net reduces parameter utilization by over 70% yet performs with neck and neck score with the original MS-Net for CIFAR-10 and CIFAR-100 dataset.","PeriodicalId":231194,"journal":{"name":"2021 5th IEEE International Conference on Cybernetics (CYBCONF)","volume":"124 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131433904","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
Parameter Optimization via CMA-ES for Implementation in the Active Control of Magnetic Pillar Arrays 基于CMA-ES的磁柱阵主动控制参数优化实现
2021 5th IEEE International Conference on Cybernetics (CYBCONF) Pub Date : 2021-06-08 DOI: 10.1109/CYBCONF51991.2021.9464138
Suparat Gaysornkaew, Danilo Vasconcellos Vargas, F. Tsumori
{"title":"Parameter Optimization via CMA-ES for Implementation in the Active Control of Magnetic Pillar Arrays","authors":"Suparat Gaysornkaew, Danilo Vasconcellos Vargas, F. Tsumori","doi":"10.1109/CYBCONF51991.2021.9464138","DOIUrl":"https://doi.org/10.1109/CYBCONF51991.2021.9464138","url":null,"abstract":"Pillared surfaces are the products of a surface modification technique that allow the implementation of active control methods by an outer source such as magnetic fields. Pillar arrays with magnetic tips exhibit different characteristics depending on the initial positional arrangement of the pillars and/or the environmental magnetic field conditions. This study develops methods for simulation and parameter optimization by machine learning to aid the investigation of pillar behaviors in various combinations of initial positions and magnetic fields. Optimization is performed using the co-variance adaptation evolution strategy (CMA-ES). The algorithm is tested to obtain preliminary results: (1) the maximum size of the pillar pitch at a given magnetic field; (2) the initial pillar arrangement of a 3-pillar unit cell and three settings of applied magnetic field–each corresponds to a predefined contact state of a three-stage paring pattern.","PeriodicalId":231194,"journal":{"name":"2021 5th IEEE International Conference on Cybernetics (CYBCONF)","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132011209","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
Automatic benign and malignant estimation of bone tumors using deep learning 基于深度学习的骨肿瘤良恶性自动估计
2021 5th IEEE International Conference on Cybernetics (CYBCONF) Pub Date : 2021-06-08 DOI: 10.1109/CYBCONF51991.2021.9464132
Kaito Furuo, Kento Morita, Tomohito Hagi, Tomoki Nakamura, T. Wakabayashi
{"title":"Automatic benign and malignant estimation of bone tumors using deep learning","authors":"Kaito Furuo, Kento Morita, Tomohito Hagi, Tomoki Nakamura, T. Wakabayashi","doi":"10.1109/CYBCONF51991.2021.9464132","DOIUrl":"https://doi.org/10.1109/CYBCONF51991.2021.9464132","url":null,"abstract":"The bone tumor causes the bone pain and swelling, and is firstly diagnosed in a local hospital in many cases. This has become a problem in recent years, and also the benign and malignant nature of bone tumors is difficult and requires a great deal of effort even for medical specialists. Therefore, the development of a system to automatically estimate the benign or malignant nature of bone tumors is required. In this study, we propose a method for automatically estimating the benignity or malignancy of bone tumors using deep learning. We fine-tuned VGG16 and ResNet152 trained on ImageNet using image patches extracted from 38 plain X-ray images of 3 patients. Results on patch-level classification showed that VGG16 achieved higher estimation accuracy (f1-score of 0.790) than ResNet152 (f1-score of 0.784). We also performed the tumor-level classification experiment in which 4 benign and 6 malignant tumors were correctly classified to the appropriate class.","PeriodicalId":231194,"journal":{"name":"2021 5th IEEE International Conference on Cybernetics (CYBCONF)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126032235","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: 3
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