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2022 International Conference on Artificial Intelligence and Computer Information Technology (AICIT)最新文献

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An Image Denoising Algorithm Based on Improved Wavelet Threshold Function 基于改进小波阈值函数的图像去噪算法
2022 International Conference on Artificial Intelligence and Computer Information Technology (AICIT) Pub Date : 2022-09-16 DOI: 10.1109/AICIT55386.2022.9930193
Fan Yang, Zihao Ye
{"title":"An Image Denoising Algorithm Based on Improved Wavelet Threshold Function","authors":"Fan Yang, Zihao Ye","doi":"10.1109/AICIT55386.2022.9930193","DOIUrl":"https://doi.org/10.1109/AICIT55386.2022.9930193","url":null,"abstract":"In the field of image denoising research, the technique of wavelet threshold denoising has been widely used. Aiming at the shortcomings of traditional hard threshold and soft threshold denoising, an improved threshold function is proposed for image denoising in this paper. Two tuning parameters are added to this threshold function to improve the flexibility of the function. In the evaluation of denoising performance, this paper uses the peak signal to noise ratio (PSNR) and mean square error (MSE) as evaluation indicators. Experimental results on Boats images show that algorithm proposed in this paper improves the PSNR by 0.1 dB and 0.12 dB and reduces the MSE by 2.35% and 2.81%, respectively, compared with the algorithms in reference [6] and reference [7]. The experimental results on other images also show that the algorithm proposed in this paper also has some improvement in evaluation indexes compared with several comparative algorithms.","PeriodicalId":231070,"journal":{"name":"2022 International Conference on Artificial Intelligence and Computer Information Technology (AICIT)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122277703","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
Deep-learning-based Adaptive Predistorter for Nonlinear LED Compensation in Visible Light Communication Systems 基于深度学习的非线性LED补偿自适应预失真器
2022 International Conference on Artificial Intelligence and Computer Information Technology (AICIT) Pub Date : 2022-09-16 DOI: 10.1109/AICIT55386.2022.9930205
Xiao-jing Shi, Huiqin Zhu, Guoqiao Li
{"title":"Deep-learning-based Adaptive Predistorter for Nonlinear LED Compensation in Visible Light Communication Systems","authors":"Xiao-jing Shi, Huiqin Zhu, Guoqiao Li","doi":"10.1109/AICIT55386.2022.9930205","DOIUrl":"https://doi.org/10.1109/AICIT55386.2022.9930205","url":null,"abstract":"In typical visible light communication (VLC) systems, light emitting diodes (LEDs) are adopted as light transmitters by modulating the optical power of LEDs with input current. However, LEDs has a well-known nonlinear distortion which cannot be ignored and would inevitably degrade the performance of VLC systems. Since the deep-learning (DL) method has a reputation for nonlinear approximation, a DL-based predistorter is proposed to mitigate the LED nonlinearity. Simulation results show that the proposed method has superior performance than existing linear predistortion methods, such as the look-up-table (LUT), normalized least mean square (NLMS) algorithms and the nonlinear predistortion method, such as the Chebyshev polynomial-based algorithm.","PeriodicalId":231070,"journal":{"name":"2022 International Conference on Artificial Intelligence and Computer Information Technology (AICIT)","volume":"208 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127097659","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
Question-Driven Multiple Attention(DQMA) Model for Visual Question Answer 问题驱动多注意(DQMA)视觉问答模型
2022 International Conference on Artificial Intelligence and Computer Information Technology (AICIT) Pub Date : 2022-09-16 DOI: 10.1109/AICIT55386.2022.9930294
Jinmeng Wu, Lei Ma, Fulin Ge, Y. Hao, Pengcheng Shu
{"title":"Question-Driven Multiple Attention(DQMA) Model for Visual Question Answer","authors":"Jinmeng Wu, Lei Ma, Fulin Ge, Y. Hao, Pengcheng Shu","doi":"10.1109/AICIT55386.2022.9930294","DOIUrl":"https://doi.org/10.1109/AICIT55386.2022.9930294","url":null,"abstract":"Visual Question and Answer (VQA) refers to a typical multimodal problem in the fields of computer vision and natural language processing, which aims to give an open-ended question about an image that can be answered accurately. The currently existing visual question answer models inevitably introduce redundant and inaccurate visual information when exploring the rich interaction between complex image targets and texts, and they also fail to focus effectively on the targets in the scene. To address this problem, the Question-Driven Multiple Attention Model (QDMA) is proposed. Firstly, Faster R-CNN and LSTM are used to extract visual features of images and textual features of questions. Then we design a question-driven attention network to obtain question regions of interest in images so that the model can accurately target relevant targets in complex scenes. To establish intensive interaction between the image region of interest and the question word, the co-attentive network consisting of self-attentive and guided-attentive units is introduced. Finally, the correct answer is obtained by inputting question features and image features into an answer prediction module consisting of two-layer Multi-Layer Perceptron. On the VQA2.0 dataset, the suggested method is empirically compared with other methods. The results reveal that the model outperforms other methods, demonstrating the usefulness of the framework.","PeriodicalId":231070,"journal":{"name":"2022 International Conference on Artificial Intelligence and Computer Information Technology (AICIT)","volume":"73 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127406478","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 remote sensing detection method for distributed subsurface targets inside mountain bodies 山体内部分布式地下目标的遥感探测方法研究
2022 International Conference on Artificial Intelligence and Computer Information Technology (AICIT) Pub Date : 2022-09-16 DOI: 10.1109/AICIT55386.2022.9930298
Wenbing Deng, Kechao Wang, Xin Liu, Tianxu Zhang, Hanyu Liu, Jianwei Liu
{"title":"Research on remote sensing detection method for distributed subsurface targets inside mountain bodies","authors":"Wenbing Deng, Kechao Wang, Xin Liu, Tianxu Zhang, Hanyu Liu, Jianwei Liu","doi":"10.1109/AICIT55386.2022.9930298","DOIUrl":"https://doi.org/10.1109/AICIT55386.2022.9930298","url":null,"abstract":"With the continuous promotion of urban modernization, the development and utilization of underground space has been widely emphasized to ensure the sustainable use of land resources. Research on the detection of underground targets can reveal the internal conditions of underground space, provide help for the planning and construction of underground space, and promote the improvement of underground facility design methods. Research on underground pipelines and other small underground target detection is also important, through detection can grasp the direction and distribution of pipelines, can timely locate the location of pipeline faults; can timely find and stop the illegal behavior of privately connected underground pipelines, and promote the improvement of urban management. At present, domestic and foreign research on underground target detection methods using remote sensing technology is mostly based on multi-temporal infrared images of underground target detection method, which has a large sample size and high difficulty in obtaining data, and the research object is limited to small underground targets with certain characteristics and shallow burial depth, which has great limitations. Therefore, this paper proposes the method of using infrared remote sensing technology to detect the distributed subsurface targets inside the mountain, and fully considers the influence of the mountain vegetation and solar radiation.","PeriodicalId":231070,"journal":{"name":"2022 International Conference on Artificial Intelligence and Computer Information Technology (AICIT)","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129642018","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
Vehicle trajectory prediction based on LSTM network 基于LSTM网络的车辆轨迹预测
2022 International Conference on Artificial Intelligence and Computer Information Technology (AICIT) Pub Date : 2022-09-16 DOI: 10.1109/AICIT55386.2022.9930177
Zhifang Yang, Dun Liu, Li Ma
{"title":"Vehicle trajectory prediction based on LSTM network","authors":"Zhifang Yang, Dun Liu, Li Ma","doi":"10.1109/AICIT55386.2022.9930177","DOIUrl":"https://doi.org/10.1109/AICIT55386.2022.9930177","url":null,"abstract":"In a complex traffic environment, predicting the trajectory of surrounding vehicles in the driver’s line of sight can greatly reduce the possibility of various traffic accidents and play an auxiliary role in the driver’s decision making. The motion of predicted vehicles is constrained by the traffic environment, that is, the motion of adjacent vehicles and the relative spatial positions between vehicles. This paper mainly studies the behavior prediction of vehicles on the expressway. Based on the social convolutional pooling LSTM network (CS-LSTM), a CS-LSTM network with an attention mechanism is proposed, which assigns different weights to the fusion features and improves the accuracy of the trajectory prediction of surrounding vehicles. This article evaluates the model on a publicly available NGSIM dataset. The results show that the proposed algorithm is more accurate than other algorithms in predicting the future trajectory of vehicles.","PeriodicalId":231070,"journal":{"name":"2022 International Conference on Artificial Intelligence and Computer Information Technology (AICIT)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128971878","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: 7
Infrared Image Generation Algorithm Based on GAN and contrastive learning 基于GAN和对比学习的红外图像生成算法
2022 International Conference on Artificial Intelligence and Computer Information Technology (AICIT) Pub Date : 2022-09-16 DOI: 10.1109/AICIT55386.2022.9930233
Hong Liu, Lei Ma
{"title":"Infrared Image Generation Algorithm Based on GAN and contrastive learning","authors":"Hong Liu, Lei Ma","doi":"10.1109/AICIT55386.2022.9930233","DOIUrl":"https://doi.org/10.1109/AICIT55386.2022.9930233","url":null,"abstract":"For the task of converting dimly lit, low luminance nighttime visible to infrared images, we propose a Contrastive Visible-Infrared Image Translation Network (CVIIT). To better distinguish and translate objects such as pedestrians and vehicles, we introduce an attention module based on class activation map in the generator and discriminator of the Generative Adversarial Network (GAN), which captures richer context information in the images. In addition, we introduce contrastive learning to align the generated images with the visible images in terms of content. Qualitative and quantitative experiments on a publicly available visible-Infrared image pairing dataset (LLVIP) show that the proposed method generates infrared images of significantly higher quality than other state-of-the-art image-to-image translation (I2IT) methods.","PeriodicalId":231070,"journal":{"name":"2022 International Conference on Artificial Intelligence and Computer Information Technology (AICIT)","volume":"55 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124423668","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
Design of Full Coverage Path Algorithm for exploration truck 勘探车全覆盖路径算法设计
2022 International Conference on Artificial Intelligence and Computer Information Technology (AICIT) Pub Date : 2022-09-16 DOI: 10.1109/AICIT55386.2022.9930287
Junwen Chen, Honghua Tan, Xu Wang
{"title":"Design of Full Coverage Path Algorithm for exploration truck","authors":"Junwen Chen, Honghua Tan, Xu Wang","doi":"10.1109/AICIT55386.2022.9930287","DOIUrl":"https://doi.org/10.1109/AICIT55386.2022.9930287","url":null,"abstract":"The survey work for urban underground pipelines is mostly carried out outdoors, and the randomness of its environment brings a lot of difficulties to the full-coverage path planning work of intelligent exploration vehicles. To adapt to the complex outdoor environment and improve the performance and efficiency of the crossing, this article constructs the exploration vehicle model and improves the traditional DFS algorithm. Changing its backtracking strategy based on the original algorithm and introducing a node cost function to linearly constrain the number of turns of the exploration vehicle. Through simulation experiments, the improved DFS algorithm can efficiently complete the full-coverage exploration task for pipeline exploration sites and compared with some classical algorithms, the improved algorithm has a significant reduction in the map traversal repetition rate, and also shows obvious advantages in solving the full-coverage path planning problem in complex environments, which can complete the related work more efficiently.","PeriodicalId":231070,"journal":{"name":"2022 International Conference on Artificial Intelligence and Computer Information Technology (AICIT)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126344679","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
Fisher’s tobacco leaf grading method based on image multi-features 基于图像多特征的Fisher烟叶分级方法
2022 International Conference on Artificial Intelligence and Computer Information Technology (AICIT) Pub Date : 2022-09-16 DOI: 10.1109/AICIT55386.2022.9930167
Shubin Yang, Chunlin Dong, Feng-ge Wang, Mi Zhou, Mengze Yuan, Jiben Huang
{"title":"Fisher’s tobacco leaf grading method based on image multi-features","authors":"Shubin Yang, Chunlin Dong, Feng-ge Wang, Mi Zhou, Mengze Yuan, Jiben Huang","doi":"10.1109/AICIT55386.2022.9930167","DOIUrl":"https://doi.org/10.1109/AICIT55386.2022.9930167","url":null,"abstract":"To address the problems of manual tobacco grading, which is influenced by subjective factors and low accuracy of discrimination, this article discusses the automatic discrimination grading method based on machine vision technology. Firstly, a total of 16 image features were extracted from the geometric, color and texture classes of tobacco leaf based on the pre-processing of the collected tobacco leaf images. Next, the Fisher discriminant analysis model for tobacco leaf grade recognition was established with 16 image features from 38 groups of samples, and the accuracy of the Fisher discriminant analysis model was 97.4%. Finally, the other 7 sets of features were used as prediction samples to test the applicability of the discriminant model. The results show that the grading method has higher accuracy and stability compared with manual tobacco leaf grading, and can effectively identify the grades of small samples of tobacco leaf.","PeriodicalId":231070,"journal":{"name":"2022 International Conference on Artificial Intelligence and Computer Information Technology (AICIT)","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116066159","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 Resource Scheduling and Virtualization of Crossdomain Unmanned Equipment Based on Microservices 基于微服务的跨域无人装备资源调度与虚拟化研究
2022 International Conference on Artificial Intelligence and Computer Information Technology (AICIT) Pub Date : 2022-09-16 DOI: 10.1109/AICIT55386.2022.9930326
Kangyi Yuan, Zhang Fan, Yi Zhao, Q. Zhu, ShangJun Li
{"title":"Research on Resource Scheduling and Virtualization of Crossdomain Unmanned Equipment Based on Microservices","authors":"Kangyi Yuan, Zhang Fan, Yi Zhao, Q. Zhu, ShangJun Li","doi":"10.1109/AICIT55386.2022.9930326","DOIUrl":"https://doi.org/10.1109/AICIT55386.2022.9930326","url":null,"abstract":"With the rapid development of unmanned technology, the use of unmanned equipment is changing from stand-alone operations to cross-domain multi-platform cluster operations. There are many cross-domain unmanned equipment resources, including unmanned surface vehicle(USV), unmanned aerial vehicles(UAV) and unmanned underwater vehicles(UUV) and other heterogeneous unmanned equipment platforms. In view of the problems of unified management, scheduling and collaborative operations of multiplatform resources in cross-domain unmanned equipment, the overall architecture and service integration method based on microservices technology is proposed, combined with containerization and other technologies, and theoretical technologies such as virtualization, service and modularization of cross-domain unmanned equipment resources are studied to build a digital model of unmanned equipment resources and realize unified management and scheduling of cross-domain unmanned equipment platform resources, service It supports the decoupling of unmanned equipment resources into services and integrated scheduling management, builds an open architecture for cross-domain unmanned equipment, supports the integration of unmanned equipment information resources sharing services, and tows the development of China’s unmanned combat force construction capabilities. Finally, the feasibility of the architecture is verified through a simulation test platform.","PeriodicalId":231070,"journal":{"name":"2022 International Conference on Artificial Intelligence and Computer Information Technology (AICIT)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132577285","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
Study Of Super-resolution Methods Based On Fitted Dual Quadratic Polynomials 基于拟合对偶二次多项式的超分辨方法研究
2022 International Conference on Artificial Intelligence and Computer Information Technology (AICIT) Pub Date : 2022-09-16 DOI: 10.1109/AICIT55386.2022.9930297
Hanyu Liu, Meng Liu, Tianxu Zhang, Wenbing Deng, Xiaotai Liu, Jianwei Liu
{"title":"Study Of Super-resolution Methods Based On Fitted Dual Quadratic Polynomials","authors":"Hanyu Liu, Meng Liu, Tianxu Zhang, Wenbing Deng, Xiaotai Liu, Jianwei Liu","doi":"10.1109/AICIT55386.2022.9930297","DOIUrl":"https://doi.org/10.1109/AICIT55386.2022.9930297","url":null,"abstract":"As an important index to measure infrared images, spatial resolution plays a key role in infrared remote sensing imaging, navigation guidance of aircraft and recognition of military targets. However, the pixel density of infrared imaging detectors is much lower than that of visible light detectors, resulting in low resolution of infrared images obtained. Infrared images also have shortcomings such as high noise, fuzzy interference and loss of high-frequency information, which affect the detection and recognition of targets. In this thesis, an infrared image super-resolution degradation model is established based on the degradation factors that occur in the infrared imaging process. The influence of noise and blur on improving the resolution of infrared images is analyzed, and in this way, a full-flow reconstruction model of infrared image super-resolution is established. On the basis of noise and blur removal,a super-resolution method based on fitted dual quadratic polynomials is proposed for the low resolution of infrared images. This method makes full use of the pixel information of the original image, and uses the fitted interpolation polynomial to expand the pixels of the low-resolution image to obtain a high-resolution image. On the basis of improving the resolution, the infrared image noise and blur are better suppressed, the detailed features are reflected and the subjective quality is improved.","PeriodicalId":231070,"journal":{"name":"2022 International Conference on Artificial Intelligence and Computer Information Technology (AICIT)","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115846716","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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