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International Conference on Artificial Intelligence and Computer Engineering (ICAICE 2022)最新文献

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Wireless communication algorithm based on radio frequency identification technology: wireless communication system design and research 基于无线通信算法的射频识别技术:无线通信系统的设计与研究
International Conference on Artificial Intelligence and Computer Engineering (ICAICE 2022) Pub Date : 2023-04-28 DOI: 10.1117/12.2680661
Xin Liu
{"title":"Wireless communication algorithm based on radio frequency identification technology: wireless communication system design and research","authors":"Xin Liu","doi":"10.1117/12.2680661","DOIUrl":"https://doi.org/10.1117/12.2680661","url":null,"abstract":"With the development of artificial intelligence technology, radio frequency identification technology is more and more widely used in wireless communication systems. This article describes an introduction to radio frequency identification technology. It also studies the design and application of wireless communication systems based on radio frequency identification technology.","PeriodicalId":227528,"journal":{"name":"International Conference on Artificial Intelligence and Computer Engineering (ICAICE 2022)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-04-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131586567","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
Does gender affect the processing of object classification in natural scenes 性别是否影响自然场景中物体分类的处理
International Conference on Artificial Intelligence and Computer Engineering (ICAICE 2022) Pub Date : 2023-04-28 DOI: 10.1117/12.2671092
Weiqiang Peng, Xin Wang, Dongjie Lang, Weina Zhu
{"title":"Does gender affect the processing of object classification in natural scenes","authors":"Weiqiang Peng, Xin Wang, Dongjie Lang, Weina Zhu","doi":"10.1117/12.2671092","DOIUrl":"https://doi.org/10.1117/12.2671092","url":null,"abstract":"Humans can quickly and efficiently extract information from a complex natural scene. Rapid detection of animals is such an example, which is fast and accurate. We can see that animals have gender differences, and human beings also have gender differences, and they all appear in our real life. Therefore, we will use a two-alternative forced-choice paradigm (2AFC) to investigate the gender differences between the two targets. In our experiment, we balanced the various factors that could be taken into account and subjected the images to histogram equalization. We analyzed the reaction time of the subjects to stimuli of the target gender (male or female). We report two main findings. First, when the type of target (human or animal) was not considered, subjects had faster reaction times to male targets than to female targets. Second, gender differences were only significant for animals when the kind of object (human or animal) was considered.","PeriodicalId":227528,"journal":{"name":"International Conference on Artificial Intelligence and Computer Engineering (ICAICE 2022)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-04-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132918915","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
Agricultural products traceability e-commerce platform based on speech recognition 基于语音识别的农产品溯源电子商务平台
International Conference on Artificial Intelligence and Computer Engineering (ICAICE 2022) Pub Date : 2023-04-28 DOI: 10.1117/12.2671343
Pei Yu, Pan Qi, Qian Wei, Lin Zhaoyu, Jin xinyu, Chen Mingzhou
{"title":"Agricultural products traceability e-commerce platform based on speech recognition","authors":"Pei Yu, Pan Qi, Qian Wei, Lin Zhaoyu, Jin xinyu, Chen Mingzhou","doi":"10.1117/12.2671343","DOIUrl":"https://doi.org/10.1117/12.2671343","url":null,"abstract":"To develop rural e-commerce, we enhance sales of agricultural products by using speech recognition technology to lower the operation threshold. We also use a QR code-based traceability system to ensure product safety. We built a traceable e-commerce platform for agricultural items-based voice recognition.","PeriodicalId":227528,"journal":{"name":"International Conference on Artificial Intelligence and Computer Engineering (ICAICE 2022)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-04-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133195969","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
Object tracking based on foreground adaptive bounding box and motion state redetection 基于前景自适应边界框和运动状态重检测的目标跟踪
International Conference on Artificial Intelligence and Computer Engineering (ICAICE 2022) Pub Date : 2023-04-28 DOI: 10.1117/12.2671281
Jingyi Fu, Qifeng Liang, Qingsong Xie, Zhiyong An
{"title":"Object tracking based on foreground adaptive bounding box and motion state redetection","authors":"Jingyi Fu, Qifeng Liang, Qingsong Xie, Zhiyong An","doi":"10.1117/12.2671281","DOIUrl":"https://doi.org/10.1117/12.2671281","url":null,"abstract":"Siamese network is successfully applied in object tracking. Most of the existing Siamese tracking methods extract template features in the first frame, which will cause the tracker to ignore the appearance change of the target in the subsequent video. In this paper, we propose a tracker based on foreground adaptive bounding box and motion state redetection. The tracker infers the reliability of tracking by the motion pattern of the bounding box. When an anomaly is detected, the tracker will redetect using the continuously updated template. Furthermore, our tracker employs an adaptive bounding box to avoid the effects of inaccurate rotation of the bounding box. The results on the VOT2018 dataset show that our tracker achieves stronger robustness and higher accuracy, providing superior performance compared to the current state-of-the-art trackers.","PeriodicalId":227528,"journal":{"name":"International Conference on Artificial Intelligence and Computer Engineering (ICAICE 2022)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-04-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114332411","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 painting image classification based on convolution neural network 基于卷积神经网络的绘画图像分类研究
International Conference on Artificial Intelligence and Computer Engineering (ICAICE 2022) Pub Date : 2023-04-28 DOI: 10.1117/12.2671523
Ruiming Zhao, Kai Liu
{"title":"Research on painting image classification based on convolution neural network","authors":"Ruiming Zhao, Kai Liu","doi":"10.1117/12.2671523","DOIUrl":"https://doi.org/10.1117/12.2671523","url":null,"abstract":"The digitalization of painting works is of great significance to the effective use of painting resources. Traditional image classification methods do not consider the subjective characteristics of painting works, and most of the features need to be manually extracted. There are problems such as loss of detail features. In this paper, a painting image classification method based on convolution neural network is proposed, and the influence of the size of convolution kernel, the structure width of convolution neural network, and the number of training samples on the classification results is analyzed to optimize the network structure and parameters. The experimental results show that the method is effective for the classification of painting images, and the classification results of different painting image data sets are also good.","PeriodicalId":227528,"journal":{"name":"International Conference on Artificial Intelligence and Computer Engineering (ICAICE 2022)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-04-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114964706","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
Upper bounds for the minimal eigenvalue of M-matrices m -矩阵的最小特征值的上界
International Conference on Artificial Intelligence and Computer Engineering (ICAICE 2022) Pub Date : 2023-04-28 DOI: 10.1117/12.2671094
Qin Zhong, Chunyan Zhao, Ling Li
{"title":"Upper bounds for the minimal eigenvalue of M-matrices","authors":"Qin Zhong, Chunyan Zhao, Ling Li","doi":"10.1117/12.2671094","DOIUrl":"https://doi.org/10.1117/12.2671094","url":null,"abstract":"According to the related M-matrix property, new upper bounds for the minimum eigenvalue of the irreducible M-matrix are provided. It is demonstrated that the new upper bound is sharper than the classical upper bound when the M-matrix is symmetric. Numerical examples further verify the validity of the results.","PeriodicalId":227528,"journal":{"name":"International Conference on Artificial Intelligence and Computer Engineering (ICAICE 2022)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-04-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117352163","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 study of stock price analysis algorithms for new energy companies based on random forest and genetic algorithms 基于随机森林和遗传算法的新能源公司股价分析算法研究
International Conference on Artificial Intelligence and Computer Engineering (ICAICE 2022) Pub Date : 2023-04-28 DOI: 10.1117/12.2671249
Shiyang Song, Junhan Gao, Anran Zhao, Yu Li, C. Li, Y. Zhu
{"title":"A study of stock price analysis algorithms for new energy companies based on random forest and genetic algorithms","authors":"Shiyang Song, Junhan Gao, Anran Zhao, Yu Li, C. Li, Y. Zhu","doi":"10.1117/12.2671249","DOIUrl":"https://doi.org/10.1117/12.2671249","url":null,"abstract":"China is the world's largest emerging energy market, but due to the rapid development of China's new energy industry special, the value of new energy companies are more susceptible to sharp increases and decreases brought about by external factors in the market compared to other companies. In this paper, we propose an algorithm that uses an effective cluster learning strategy (Random Forest) contrasted with a genetic algorithm. A new financial forecasting model GSRF is constructed by parameter optimization of random forest model through grid search algorithm, and the model is applied to short-term stock forecasting. This paper builds a stock price trend forecasting model based on both algorithms and uses the model to determine whether the cost of a stock will be higher than its cost at a given date. The experimental results show that the model built using GSRF stochastic forest has the highest return and the lowest risk compared to the return based on the traditional genetic algorithm trading strategy.","PeriodicalId":227528,"journal":{"name":"International Conference on Artificial Intelligence and Computer Engineering (ICAICE 2022)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-04-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123572735","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 intelligent agricultural decision-making system based on Bayesian optimization 基于贝叶斯优化的智能农业决策系统研究
International Conference on Artificial Intelligence and Computer Engineering (ICAICE 2022) Pub Date : 2023-04-28 DOI: 10.1117/12.2671265
Xiaoying Yan
{"title":"Research on intelligent agricultural decision-making system based on Bayesian optimization","authors":"Xiaoying Yan","doi":"10.1117/12.2671265","DOIUrl":"https://doi.org/10.1117/12.2671265","url":null,"abstract":"Along with social development, the problems of insufficient rural labor and mismatch between labor intensity and economic returns have become a greater obstacle to rural development; therefore, the development of agricultural intelligence to improve agricultural productivity will become the new direction of modern agricultural development. Based on internet technology, intelligent agriculture adopts digital technologies such as intelligent perception, network transmission and big data processing to provide decision basis for agricultural planting, production and pest control, or directly deploy decision information to automated farm equipment, so as to use agricultural resources reasonably and efficiently. However, the development of smart agriculture is constrained by the low accuracy of automation control and decision information. In this paper, we optimize the threshold value of each agricultural production decision data through machine learning algorithm, use Bayesian optimization to learn the agricultural production environment and crop growth data, iteratively optimize the threshold value to get the global best value, improve the accuracy of automation control and reduce the risk of agricultural production decision, and effectively improve the economic returns of agriculture.","PeriodicalId":227528,"journal":{"name":"International Conference on Artificial Intelligence and Computer Engineering (ICAICE 2022)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-04-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125892999","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
Short-term traffic flow prediction of BP based on adaptive BWO optimization 基于自适应BWO优化的BP短期交通流预测
International Conference on Artificial Intelligence and Computer Engineering (ICAICE 2022) Pub Date : 2023-04-28 DOI: 10.1117/12.2671041
Fuyou Mao, Limei Sun, Xiyang Liu
{"title":"Short-term traffic flow prediction of BP based on adaptive BWO optimization","authors":"Fuyou Mao, Limei Sun, Xiyang Liu","doi":"10.1117/12.2671041","DOIUrl":"https://doi.org/10.1117/12.2671041","url":null,"abstract":"Accurate short-term traffic flow prediction is the basis and key to the intelligent transportation system. With the continuous development of machine learning algorithms and the latest swarm intelligence algorithms, a reasonable combination of the two will produce a good prediction effect. In this paper, BP neural network algorithm in the short-term traffic flow prediction problem accuracy is not high and easy to fall into the local minimum and so on. This paper established a BP based on adaptive BWO optimization short-term traffic flow prediction model, first of all, to carry on the data preprocessing the data set and divided into the training set and test set, and then the data for training, the best model to forecast practical optimization results, finally the model prediction results were compared with the rest of the 6 kinds of classical model. The experimental results show that the optimized BP model based on adaptive BWO can achieve a good traffic flow prediction effect in the short term, MAE is 7.357, MSE is 102.772, and R2 is 0.889, which are better than the other six models.","PeriodicalId":227528,"journal":{"name":"International Conference on Artificial Intelligence and Computer Engineering (ICAICE 2022)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-04-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128389621","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
Tomato identification and picking point location based on YOLOv5 基于YOLOv5的番茄识别与采摘点定位
International Conference on Artificial Intelligence and Computer Engineering (ICAICE 2022) Pub Date : 2023-04-28 DOI: 10.1117/12.2671180
Chengyuan Song, Chao Wang, Jian-ying Song
{"title":"Tomato identification and picking point location based on YOLOv5","authors":"Chengyuan Song, Chao Wang, Jian-ying Song","doi":"10.1117/12.2671180","DOIUrl":"https://doi.org/10.1117/12.2671180","url":null,"abstract":"The traditional tomato detection method of image segmentation is complex, and it is easy to be blocked by branches and leaves, fruit overlapping and other reasons, which affect the detection accuracy of fruit and the accurate positioning of picking points. This study proposes a fast identification and localization method of tomato based on YOLOv5 network. This method performs end-to-end detection by traversing the entire image with a single convolutional neural network, returning the class and location of the object. On the basis of YOLOv5, the regression box loss function is modified to improve the detection effect of tomato fruit, and the center point of the fruit boundary rectangle detected by YOLOv5 is used as the center point of tomato picking. The experimental results show that the average localization error of the proposed method is 1.379%, which is 1.867% lower than the traditional Hough method. The YOLOv5 method can effectively identify tomato fruits in natural environment. It can effectively detect tomatoes in overlapping, small targets, immature and other scenes, and perform more accurate positioning, laying a foundation for the tomato picking robot to select the best picking point.","PeriodicalId":227528,"journal":{"name":"International Conference on Artificial Intelligence and Computer Engineering (ICAICE 2022)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-04-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128225129","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
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