2022 4th International Conference on Artificial Intelligence and Advanced Manufacturing (AIAM)最新文献

Face Skin Color Detection Method Based on YUV-KL Transform 基于YUV-KL变换的人脸肤色检测方法

2022 4th International Conference on Artificial Intelligence and Advanced Manufacturing (AIAM) Pub Date : 2022-10-01 DOI: 10.1109/AIAM57466.2022.00109

Yiping Chen, Fengshan Yuan

引用次数: 0

Research on Optimization of Human-Skilled Matching of SMEs Based on Ant Colony Optimization Algorithm 基于蚁群优化算法的中小企业人力技能匹配优化研究

2022 4th International Conference on Artificial Intelligence and Advanced Manufacturing (AIAM) Pub Date : 2022-10-01 DOI: 10.1109/AIAM57466.2022.00025

Chang Qu

引用次数: 0

Optimization of Vaccine Production in Workshop Based on Genetic Algorithm 基于遗传算法的车间疫苗生产优化

2022 4th International Conference on Artificial Intelligence and Advanced Manufacturing (AIAM) Pub Date : 2022-10-01 DOI: 10.1109/AIAM57466.2022.00093

Danhong Wu, Can Huang, Huazhou Zeng, Yujing Zhao

{"title":"Optimization of Vaccine Production in Workshop Based on Genetic Algorithm","authors":"Danhong Wu, Can Huang, Huazhou Zeng, Yujing Zhao","doi":"10.1109/AIAM57466.2022.00093","DOIUrl":"https://doi.org/10.1109/AIAM57466.2022.00093","url":null,"abstract":"In the face of some infectious diseases raging all over the world, the efficiency of vaccine production directly affects the ability of medical staff to rescue patients and the timeliness of global epidemic prevention. Therefore, it is of great significance to establish an optimal planning model from the production source to minimize the time required for vaccine production without affecting the quality of vaccine production. This paper analyzes and discusses the problem of vaccine production from two aspects. Firstly, under ideal conditions, without considering the impact of vaccine production time, based on the average time of producing each box of vaccine at each station, a scheduling optimization model with multi-objective constraints is established, and then the flow shop scheduling model (FSP) of genetic algorithm is used to solve it. We estimate that the gene assignment adopts a classical roulette algorithm, the gene crossover part adopts the partial mapping crossover algorithm, and the gene mutation step uses the gene reverse order algorithm to simulate the operation of the stack. In practice, the time required to produce each vaccine at each station is random. Bring in the normal probability distribution function, improve the genetic algorithm and shorten the total time by 5%.","PeriodicalId":439903,"journal":{"name":"2022 4th International Conference on Artificial Intelligence and Advanced Manufacturing (AIAM)","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124948398","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, Analysis and Verification of New Vehiclemounted Antenna Lifting Platform 新型车载天线升降平台的设计、分析与验证

2022 4th International Conference on Artificial Intelligence and Advanced Manufacturing (AIAM) Pub Date : 2022-10-01 DOI: 10.1109/AIAM57466.2022.00064

Pengcheng Kong, Liang Cai, Sihua Zhang

引用次数: 0

Face recognition based on principal component analysis (PCA) 基于主成分分析的人脸识别

2022 4th International Conference on Artificial Intelligence and Advanced Manufacturing (AIAM) Pub Date : 2022-10-01 DOI: 10.1109/AIAM57466.2022.00185

Caihua Qiu, Feng Ding

引用次数: 1

Image processing technology based on computer vision algorithm 基于计算机视觉算法的图像处理技术

2022 4th International Conference on Artificial Intelligence and Advanced Manufacturing (AIAM) Pub Date : 2022-10-01 DOI: 10.1109/AIAM57466.2022.00172

Mengxia Fan, Yunna Liu

{"title":"Image processing technology based on computer vision algorithm","authors":"Mengxia Fan, Yunna Liu","doi":"10.1109/AIAM57466.2022.00172","DOIUrl":"https://doi.org/10.1109/AIAM57466.2022.00172","url":null,"abstract":"Under the background of information age, image processing technology is a commonly used technology in all walks of life. In order to improve the image correction effect, it can be processed based on computer vision algorithm. This paper introduces the image categories and technical characteristics of computer vision algorithm and image processing technology, discusses the image processing technology based on computer vision algorithm, including computer vision display system and image distortion correction two parts, the effect is good, has high application value. In the past, due to the lack of technological development, objects in the traditional two-dimensional environment can only display the side projection, relatively single, in order to adapt to social progress, technology will continue to develop, so three-dimensional three-dimensional picture emerged at the historic moment, a new display technology appeared. In order to obtain the ideal visual effect, technicians need to implement image processing technology on the basis of computer vision algorithm, express the actual coordinates of objects in three-dimensional space with three-dimensional voxels, and correct the distorted image caused by projection. Compared with the traditional BP neural network, the image processing technology based on computer vision algorithm obviously has more advantages and higher accuracy.","PeriodicalId":439903,"journal":{"name":"2022 4th International Conference on Artificial Intelligence and Advanced Manufacturing (AIAM)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128316581","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 the reliability of automotive sensors based on minimum relative information entropy 基于最小相对信息熵的汽车传感器可靠性研究

2022 4th International Conference on Artificial Intelligence and Advanced Manufacturing (AIAM) Pub Date : 2022-10-01 DOI: 10.1109/AIAM57466.2022.00125

Tao Liu, Duwei Gong

引用次数: 0

Driving Structure Design and Analysis of Multi- DOF Bionic Flapping Wing Aircraft 多自由度仿生扑翼飞行器驱动结构设计与分析

2022 4th International Conference on Artificial Intelligence and Advanced Manufacturing (AIAM) Pub Date : 2022-10-01 DOI: 10.1109/AIAM57466.2022.00133

Longyue Chai, Zilei Yang

{"title":"Driving Structure Design and Analysis of Multi- DOF Bionic Flapping Wing Aircraft","authors":"Longyue Chai, Zilei Yang","doi":"10.1109/AIAM57466.2022.00133","DOIUrl":"https://doi.org/10.1109/AIAM57466.2022.00133","url":null,"abstract":"In order to improve the flight performance of flapping-wing aircraft, a new multi-degree-of-freedom bionic flapping-wing driving mechanism is designed based on the flight motion characteristics of gulls: The dual-crank and dual-rocker mechanism is used as the driving mechanism, and the two- segment wing structure is used as the wing to realize the expansion and folding function of the wing. The planar double crank rocker mechanism and spatial crank rocker mechanism are coupled through bevel gears so that the aileron can twist during wing flapping. The whole moving process is only driven by a DC brushless motor with a simple structure and high flight efficiency. Firstly, the kinematic model of flapping-wing vehicle driving mechanism is established through kinematic analysis. Then, the simulation analysis model of the flapping-wing mechanism is established in ADAMS simulation software, which verifies the theoretical analysis. The results show that the designed driving mechanism can realize multi-degree-of- freedom coupling motion of flapping, torsion, and folding by single-degree-of-freedom driving. The upper flapping limit is 22.6°, the lower flapping limit is -21.5°, the maximum torsion angle is 10.5°, the minimum torsion angle is -16.6°, and the folding angle range is 144.7°~192.1°. The output trajectory is the same as the wingtip trajectory of the seagull when flying and has good aerodynamic performance. The kinematic parameters obtained from the simulation are consistent with the theoretical calculation, which verifies the correctness of the theoretical calculation.","PeriodicalId":439903,"journal":{"name":"2022 4th International Conference on Artificial Intelligence and Advanced Manufacturing (AIAM)","volume":"53 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123155353","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

The study of system-interferences in ship UWB communications 舰船超宽带通信系统干扰研究

2022 4th International Conference on Artificial Intelligence and Advanced Manufacturing (AIAM) Pub Date : 2022-10-01 DOI: 10.1109/AIAM57466.2022.00110

Guo Yi, Zhang Yong, Zhuang Jiaping

引用次数: 0

Video Person Re-identification Based on Transformer-CNN Model 基于变压器- cnn模型的视频人物再识别

2022 4th International Conference on Artificial Intelligence and Advanced Manufacturing (AIAM) Pub Date : 2022-10-01 DOI: 10.1109/AIAM57466.2022.00091

Liang Zhao, Qiongfang Yu, Yi Yang

{"title":"Video Person Re-identification Based on Transformer-CNN Model","authors":"Liang Zhao, Qiongfang Yu, Yi Yang","doi":"10.1109/AIAM57466.2022.00091","DOIUrl":"https://doi.org/10.1109/AIAM57466.2022.00091","url":null,"abstract":"To overcome the problems of pose variation, complex background and more occlusion in video person re-identification, a network model ResTNet based on convolutional neural network and Transformer was proposed. ResNet50 network was used to obtain local features and the output of its middle layer was input to Transformer as prior knowledge in ResTNet. In the Transformer branch, the size of the feature map was continuously reduced. The field of perception was expanded to fully explore the relationships among local features, and generated global features of pedestrians. The model computation was also decreased with the shift window method. Cross-entropy loss and triplet loss were used to optimize the model for the two branches during training, respectively. The Rank-1 and mAP on the large-scale MARS dataset reached 86.8% and 80.3%, respectively, which were 3.8% and 3.3% higher than the benchmark. The Transformer model was not only successfully applied to the field of video person re-identification, but also extensive experiments on several large datasets showed that the proposed ResTNet network can enhance the robustness of the recognition and improve the accuracy of person re-identification effectively.","PeriodicalId":439903,"journal":{"name":"2022 4th International Conference on Artificial Intelligence and Advanced Manufacturing (AIAM)","volume":"347 ","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"113998042","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