Pub Date : 2020-06-01DOI: 10.1109/ICAICA50127.2020.9182504
Zhongyao Wan, Leiqing Dai
Speaker recognition is a newly developed recognition field in the field of speech recognition. In recent years, with the increasingly wide use of artificial neural networks, a speaker recognition method based on the BP neural network has been proposed. The main purpose of this paper is to use BP neural network to train and classify the extracted Mel Frequency Cepstrum Coefficients (MFCC) which can be seen as a kind of speech feature information, so as to achieve the function of speaker recognition.
{"title":"Speaker recognition based on BP neural network","authors":"Zhongyao Wan, Leiqing Dai","doi":"10.1109/ICAICA50127.2020.9182504","DOIUrl":"https://doi.org/10.1109/ICAICA50127.2020.9182504","url":null,"abstract":"Speaker recognition is a newly developed recognition field in the field of speech recognition. In recent years, with the increasingly wide use of artificial neural networks, a speaker recognition method based on the BP neural network has been proposed. The main purpose of this paper is to use BP neural network to train and classify the extracted Mel Frequency Cepstrum Coefficients (MFCC) which can be seen as a kind of speech feature information, so as to achieve the function of speaker recognition.","PeriodicalId":113564,"journal":{"name":"2020 IEEE International Conference on Artificial Intelligence and Computer Applications (ICAICA)","volume":"71 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126409739","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}
Pub Date : 2020-06-01DOI: 10.1109/ICAICA50127.2020.9182701
Zhenchuan Sun, Jiasheng Zhang
DC microgrids have been widely applied in the power systems. DC-DC converters are applied in parallel to realize the transform of energy from the distributed generations (DGs) to the DC bus in the circuit structure of the DC microgrid. Besides the control of the constant dc bus voltage accompany with the average current control the minimization of the power loss is an important problem of the control system of the DC microgrid. There is a contradiction between the average current control and the minimization of the power loss which shows that there is a relatively large power loss on the condition that the average current control is appiled. Contradictory equations are applied to indicate the phenomenon in a mathematical sense. By use of the generalized inverse of matrix and the method of Lagrange multipliers we can get the minimum norm and least squares solution with the average current and the given dc bus voltage. The correctness and validity of the proposed method are tested in the calculating example and simulation results.
{"title":"Research on the Minimization of the Power Loss of the DC Microgrids based on the Generalized Inverse of Matrix","authors":"Zhenchuan Sun, Jiasheng Zhang","doi":"10.1109/ICAICA50127.2020.9182701","DOIUrl":"https://doi.org/10.1109/ICAICA50127.2020.9182701","url":null,"abstract":"DC microgrids have been widely applied in the power systems. DC-DC converters are applied in parallel to realize the transform of energy from the distributed generations (DGs) to the DC bus in the circuit structure of the DC microgrid. Besides the control of the constant dc bus voltage accompany with the average current control the minimization of the power loss is an important problem of the control system of the DC microgrid. There is a contradiction between the average current control and the minimization of the power loss which shows that there is a relatively large power loss on the condition that the average current control is appiled. Contradictory equations are applied to indicate the phenomenon in a mathematical sense. By use of the generalized inverse of matrix and the method of Lagrange multipliers we can get the minimum norm and least squares solution with the average current and the given dc bus voltage. The correctness and validity of the proposed method are tested in the calculating example and simulation results.","PeriodicalId":113564,"journal":{"name":"2020 IEEE International Conference on Artificial Intelligence and Computer Applications (ICAICA)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128032818","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}
Halbach array is a hot research topic for motor researchers in recent years. With the aid of finite element analysis method, the traditional Halbach, uneven thickness Halbach and soft magnetic Halbach are compared and studied under the same amount of permanent magnets. The air gap magnetic density, AC-DC axis inductance and reluctance torque of the three Halbach arrays are analyzed. The simulation results show that the traditional Halbach motor has the largest air gap magnetic density but does not have reluctance torque. The air gap magnetic density of Halbach motor with nonuniform thickness and unequal thickness is the smallest, but reluctance torque is generated due to unequal inductance of AC and DC axis. The motor with soft magnetic Halbach not only has larger air gap magnetic density, but also has larger reluctance torque.
{"title":"Influence of Different Halbach Arrays on Performance of Permanent Magnet Synchronous Motors","authors":"Licong Duan, Hailing Lu, Chaohui Zhao, Hebiao Shen","doi":"10.1109/ICAICA50127.2020.9182625","DOIUrl":"https://doi.org/10.1109/ICAICA50127.2020.9182625","url":null,"abstract":"Halbach array is a hot research topic for motor researchers in recent years. With the aid of finite element analysis method, the traditional Halbach, uneven thickness Halbach and soft magnetic Halbach are compared and studied under the same amount of permanent magnets. The air gap magnetic density, AC-DC axis inductance and reluctance torque of the three Halbach arrays are analyzed. The simulation results show that the traditional Halbach motor has the largest air gap magnetic density but does not have reluctance torque. The air gap magnetic density of Halbach motor with nonuniform thickness and unequal thickness is the smallest, but reluctance torque is generated due to unequal inductance of AC and DC axis. The motor with soft magnetic Halbach not only has larger air gap magnetic density, but also has larger reluctance torque.","PeriodicalId":113564,"journal":{"name":"2020 IEEE International Conference on Artificial Intelligence and Computer Applications (ICAICA)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121938869","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}
Pub Date : 2020-06-01DOI: 10.1109/ICAICA50127.2020.9182472
Pengcheng Yang, Jun Zhang
In recent years, named entity recognition (NER) on user-generated content (UGC) has attracted extensive attention due to its potential widespread application prospects, such as breaking news detection and products recommendation. In this paper, we present a novel knowledge-enhanced neural sequence labelling model (KNSLM), which incorporates external entity knowledge to augment the understanding of UGC with character, word and external entity knowledge. The proposed KNSLM model addresses both text denormalization and data sparsity issues, which cannot be solved directly by current sequence labelling methods. We empirically show that this KNSLM model relieves such issues, which obtaining excellent results in UGC dataset on User-generated Text (WNUT-2017). The experimental results show this KNSLM model achieves entity and surface F1 score 55.09% and 53.12%, respectively.
{"title":"A Knowledge-Enhanced Neural Sequence Labelling Model for Named Entity Recognition on Noisy User-Generated Contents","authors":"Pengcheng Yang, Jun Zhang","doi":"10.1109/ICAICA50127.2020.9182472","DOIUrl":"https://doi.org/10.1109/ICAICA50127.2020.9182472","url":null,"abstract":"In recent years, named entity recognition (NER) on user-generated content (UGC) has attracted extensive attention due to its potential widespread application prospects, such as breaking news detection and products recommendation. In this paper, we present a novel knowledge-enhanced neural sequence labelling model (KNSLM), which incorporates external entity knowledge to augment the understanding of UGC with character, word and external entity knowledge. The proposed KNSLM model addresses both text denormalization and data sparsity issues, which cannot be solved directly by current sequence labelling methods. We empirically show that this KNSLM model relieves such issues, which obtaining excellent results in UGC dataset on User-generated Text (WNUT-2017). The experimental results show this KNSLM model achieves entity and surface F1 score 55.09% and 53.12%, respectively.","PeriodicalId":113564,"journal":{"name":"2020 IEEE International Conference on Artificial Intelligence and Computer Applications (ICAICA)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127920914","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}
Pub Date : 2020-06-01DOI: 10.1109/ICAICA50127.2020.9182551
Wei Shen
With the continuous improvement of manufacturing automation in China, traditional processing methods have been unable to meet the needs of social development. Advanced industrial robots have gradually replaced manual operation and are applied in various fields of manufacturing industry. In this paper, the robot Studio software developed by ABB company is used for manual off-line programming and virtual simulation design of ABB welding robot. It is of great significance to build a virtual simulation system of robot welding operation through the off-line programming software of robot studio, reasonably plan and configure production resources, shorten the development cycle of production line, save operation time and improve work efficiency.
{"title":"Research on virtual simulation design of ABB robot welding operation based on Robotstudio","authors":"Wei Shen","doi":"10.1109/ICAICA50127.2020.9182551","DOIUrl":"https://doi.org/10.1109/ICAICA50127.2020.9182551","url":null,"abstract":"With the continuous improvement of manufacturing automation in China, traditional processing methods have been unable to meet the needs of social development. Advanced industrial robots have gradually replaced manual operation and are applied in various fields of manufacturing industry. In this paper, the robot Studio software developed by ABB company is used for manual off-line programming and virtual simulation design of ABB welding robot. It is of great significance to build a virtual simulation system of robot welding operation through the off-line programming software of robot studio, reasonably plan and configure production resources, shorten the development cycle of production line, save operation time and improve work efficiency.","PeriodicalId":113564,"journal":{"name":"2020 IEEE International Conference on Artificial Intelligence and Computer Applications (ICAICA)","volume":"76 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132244216","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}
Pub Date : 2020-06-01DOI: 10.1109/ICAICA50127.2020.9182563
Changjin Li, Jian Cao, Xing Zhang
Night vision technology provides an important means for night observation by using infrared radiation of the target as the imaging basis. Recently, artificial neural network (ANN) has become a research hotspot. Realizing the classification and recognition of infrared images by ANN is helpful to the intelligent development of night vision technology, as well as improve the accurate judgment of the surrounding environment by unmanned vehicles at night, and better ensure the safety of people and vehicles. However, the existing infrared image data set contains a small number of images, and the types of scenes and targets presented in the images are single, which cannot support the training of ANN. ANN cannot obtain the classification function of infrared images through full learning. In this paper, an infrared image generative model based on generative adversarial network (GAN) is proposed, which can convert the existing visible light data set into the infrared version of the data set in a short time, and then solve the problem of lack of infrared image data sets. To train ResNet by infrared version data set can realize its classification function for infrared images. The model with the existing image generative model is compared through several evaluation indexes. The results show that the model is more effective in generative infrared images. Inputting ImageNet data set into this model can generate ImageNet infrared version data set. ResNet trained by this data set has a classification and recognition accuracy of 91.28%, which is higher than the experimental results of existing image generative models. The design and implementation of infrared image generative model in this paper promote the application of artificial intelligence and depth learning in night vision technology and other fields.
{"title":"Design and Implementation of an Infrared Image Generative Model","authors":"Changjin Li, Jian Cao, Xing Zhang","doi":"10.1109/ICAICA50127.2020.9182563","DOIUrl":"https://doi.org/10.1109/ICAICA50127.2020.9182563","url":null,"abstract":"Night vision technology provides an important means for night observation by using infrared radiation of the target as the imaging basis. Recently, artificial neural network (ANN) has become a research hotspot. Realizing the classification and recognition of infrared images by ANN is helpful to the intelligent development of night vision technology, as well as improve the accurate judgment of the surrounding environment by unmanned vehicles at night, and better ensure the safety of people and vehicles. However, the existing infrared image data set contains a small number of images, and the types of scenes and targets presented in the images are single, which cannot support the training of ANN. ANN cannot obtain the classification function of infrared images through full learning. In this paper, an infrared image generative model based on generative adversarial network (GAN) is proposed, which can convert the existing visible light data set into the infrared version of the data set in a short time, and then solve the problem of lack of infrared image data sets. To train ResNet by infrared version data set can realize its classification function for infrared images. The model with the existing image generative model is compared through several evaluation indexes. The results show that the model is more effective in generative infrared images. Inputting ImageNet data set into this model can generate ImageNet infrared version data set. ResNet trained by this data set has a classification and recognition accuracy of 91.28%, which is higher than the experimental results of existing image generative models. The design and implementation of infrared image generative model in this paper promote the application of artificial intelligence and depth learning in night vision technology and other fields.","PeriodicalId":113564,"journal":{"name":"2020 IEEE International Conference on Artificial Intelligence and Computer Applications (ICAICA)","volume":"99 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131814675","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}
Pub Date : 2020-06-01DOI: 10.1109/ICAICA50127.2020.9182597
Zhiqiang Zhang, Li Gao, Yangyang Xiang
Rugby is a fair compete fullfed with human discipline, self-control, and mutual respect between athletes. Notably, tackle action is one of the most basic rugby actions and the smallest unit of body touch and confrontation when attacker and defender fight for possession of rugby. After match, trainer usually count the number of tackle action happened during match to analyze and discuss for adjusting rugby tactics. This paper studies a method that optimized BP neural network based on genetic algorithm and build a neural network classifier through extracting 10-dimension gray characteristics of samples and 12-dimension geometric characteristics of body to recognize and count the tackle action. After further optimizing network structure and weights, experimental results show that our model could tackle action happened in match to avoid the subjective and empirical nature of artificial viewing discrimination with strong practical value, and will greatly improve the efficiency of trainers' work.
{"title":"Application of Optimized BP Neural Network Based on Genetic Algorithm in Rugby Tackle Action Recognition","authors":"Zhiqiang Zhang, Li Gao, Yangyang Xiang","doi":"10.1109/ICAICA50127.2020.9182597","DOIUrl":"https://doi.org/10.1109/ICAICA50127.2020.9182597","url":null,"abstract":"Rugby is a fair compete fullfed with human discipline, self-control, and mutual respect between athletes. Notably, tackle action is one of the most basic rugby actions and the smallest unit of body touch and confrontation when attacker and defender fight for possession of rugby. After match, trainer usually count the number of tackle action happened during match to analyze and discuss for adjusting rugby tactics. This paper studies a method that optimized BP neural network based on genetic algorithm and build a neural network classifier through extracting 10-dimension gray characteristics of samples and 12-dimension geometric characteristics of body to recognize and count the tackle action. After further optimizing network structure and weights, experimental results show that our model could tackle action happened in match to avoid the subjective and empirical nature of artificial viewing discrimination with strong practical value, and will greatly improve the efficiency of trainers' work.","PeriodicalId":113564,"journal":{"name":"2020 IEEE International Conference on Artificial Intelligence and Computer Applications (ICAICA)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131236051","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}
Pub Date : 2020-06-01DOI: 10.1109/ICAICA50127.2020.9182553
Yuyong Chen
In order to improve the detection and mining ability of cloud data block chain in distributed wireless communication network, a dynamic mining method of cloud data in distributed wireless communication network based on fuzzy analytic hierarchy process (AHP) is proposed. The heterogeneous storage structure model of cloud data in distributed wireless communication network is constructed. Fuzzy distributed detection method is used to detect the dynamic incremental characteristics of cloud data in distributed wireless communication network, and the distribution feature of association rules in distributed wireless communication network cloud data is extracted, and the block fuzzy feature matching fusion clustering method is used to cluster the cloud data packet chain in distributed wireless communication network. The cloud data packet block chain detection and recognition in distributed wireless communication network are carried out in the block fuzzy feature matching fusion clustering center, and the dynamic mining of cloud data in distributed wireless communication network is realized by combining fuzzy analytic hierarchy process (AHP). The simulation results show that the accuracy of cloud data dynamic mining in distributed wireless communication network is high, the precision of data mining is high, and the recognition ability is good.
{"title":"Research on dynamic mining of cloud data based on fuzzy analytic hierarchy process","authors":"Yuyong Chen","doi":"10.1109/ICAICA50127.2020.9182553","DOIUrl":"https://doi.org/10.1109/ICAICA50127.2020.9182553","url":null,"abstract":"In order to improve the detection and mining ability of cloud data block chain in distributed wireless communication network, a dynamic mining method of cloud data in distributed wireless communication network based on fuzzy analytic hierarchy process (AHP) is proposed. The heterogeneous storage structure model of cloud data in distributed wireless communication network is constructed. Fuzzy distributed detection method is used to detect the dynamic incremental characteristics of cloud data in distributed wireless communication network, and the distribution feature of association rules in distributed wireless communication network cloud data is extracted, and the block fuzzy feature matching fusion clustering method is used to cluster the cloud data packet chain in distributed wireless communication network. The cloud data packet block chain detection and recognition in distributed wireless communication network are carried out in the block fuzzy feature matching fusion clustering center, and the dynamic mining of cloud data in distributed wireless communication network is realized by combining fuzzy analytic hierarchy process (AHP). The simulation results show that the accuracy of cloud data dynamic mining in distributed wireless communication network is high, the precision of data mining is high, and the recognition ability is good.","PeriodicalId":113564,"journal":{"name":"2020 IEEE International Conference on Artificial Intelligence and Computer Applications (ICAICA)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132169398","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}
Pub Date : 2020-06-01DOI: 10.1109/ICAICA50127.2020.9181857
Chang Xu, Wen Quan, Yafei Song, Yahang Wang
With Its Calculation Method Based on the Natural Advantages of the Human Brain's Way of Thinking, Deep Learning Has a Great Advantage Over Traditional Methods for Image Recognition, Voice Recognition, and Text Processing. This Paper Uses Deep Neural Networks To Train Convolutional Neural Networks on Image Data Obtained From Unmanned Aerial Vehicles. in Addressing the Three Major Problems of the Original Model,i.e., Overfitting, Redundancy Recognition, and Low Recognition Accuracy, We Propose a Model Based on Characteristics of Images Acquired From Unmanned Aerial Vehicles, and Intelligently Generate a Set of Neural Networks that Can Quickly Recognize Multiple Types of Targets on the Battlefield. An Experiment Analyzes the Advantages and Disadvantages in Deep Learning Using Two Typical Models: Faster-Rcnn and Yolo v3. We Obtain Scenarios Applicable To Each Model, and Optimize and Improve the Recognition Accuracy of Faster-Rcnn. the Effectiveness of Our Algorithm Is Validated on a Large Experimental Dataset.
{"title":"An Optimal Faster-RCNN Algorithm for Intelligent Battlefield Target Recognition","authors":"Chang Xu, Wen Quan, Yafei Song, Yahang Wang","doi":"10.1109/ICAICA50127.2020.9181857","DOIUrl":"https://doi.org/10.1109/ICAICA50127.2020.9181857","url":null,"abstract":"With Its Calculation Method Based on the Natural Advantages of the Human Brain's Way of Thinking, Deep Learning Has a Great Advantage Over Traditional Methods for Image Recognition, Voice Recognition, and Text Processing. This Paper Uses Deep Neural Networks To Train Convolutional Neural Networks on Image Data Obtained From Unmanned Aerial Vehicles. in Addressing the Three Major Problems of the Original Model,i.e., Overfitting, Redundancy Recognition, and Low Recognition Accuracy, We Propose a Model Based on Characteristics of Images Acquired From Unmanned Aerial Vehicles, and Intelligently Generate a Set of Neural Networks that Can Quickly Recognize Multiple Types of Targets on the Battlefield. An Experiment Analyzes the Advantages and Disadvantages in Deep Learning Using Two Typical Models: Faster-Rcnn and Yolo v3. We Obtain Scenarios Applicable To Each Model, and Optimize and Improve the Recognition Accuracy of Faster-Rcnn. the Effectiveness of Our Algorithm Is Validated on a Large Experimental Dataset.","PeriodicalId":113564,"journal":{"name":"2020 IEEE International Conference on Artificial Intelligence and Computer Applications (ICAICA)","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132431999","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}
Pub Date : 2020-06-01DOI: 10.1109/ICAICA50127.2020.9182463
Chunli Liu, Junfeng Li
From the perspective of user experience combined with computer vision technology to analyzed the preference of target user's in the inlaid silver pattern of mahogany, in order to promote the inheritance and development of this intangible cultural heritage. Firstly, using the morphological analysis method and the principle of semiotics to analysis and deconstruction of the pattern of mahogany inlaid silver products, Identify key features. Construct a “mahogany inlaid silver pattern DNA model” and extract the core pattern as an experimental sample. Secondly, 40 target users of different ages and genders were selected as the subjects, using eye tracker to collect the eye movement data when the subjects observeing different patterns. Through the visual analysis of the data, discuss the relationship between the eye movement characteristics, the beauty of the pattern and the user's preference. Results show that the user's preference for patterns is greatly influenced by gender and less affected by age. Users of the same gender and different age have similar preferences for patterns. Based on the experimental results, the corresponding relationship between age, gender and pattern preference is given, which provides a reference for designers to conduct personalized design for different users and improve the success rate of products.
{"title":"Aesthetic Analysis of Mahogany Inlaid Silver Pattern Based on Eye Movement Data","authors":"Chunli Liu, Junfeng Li","doi":"10.1109/ICAICA50127.2020.9182463","DOIUrl":"https://doi.org/10.1109/ICAICA50127.2020.9182463","url":null,"abstract":"From the perspective of user experience combined with computer vision technology to analyzed the preference of target user's in the inlaid silver pattern of mahogany, in order to promote the inheritance and development of this intangible cultural heritage. Firstly, using the morphological analysis method and the principle of semiotics to analysis and deconstruction of the pattern of mahogany inlaid silver products, Identify key features. Construct a “mahogany inlaid silver pattern DNA model” and extract the core pattern as an experimental sample. Secondly, 40 target users of different ages and genders were selected as the subjects, using eye tracker to collect the eye movement data when the subjects observeing different patterns. Through the visual analysis of the data, discuss the relationship between the eye movement characteristics, the beauty of the pattern and the user's preference. Results show that the user's preference for patterns is greatly influenced by gender and less affected by age. Users of the same gender and different age have similar preferences for patterns. Based on the experimental results, the corresponding relationship between age, gender and pattern preference is given, which provides a reference for designers to conduct personalized design for different users and improve the success rate of products.","PeriodicalId":113564,"journal":{"name":"2020 IEEE International Conference on Artificial Intelligence and Computer Applications (ICAICA)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127060387","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}
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