发布求助
文献互助 智能选刊 最新文献

2021 International Conference on Computer Engineering and Artificial Intelligence (ICCEAI)最新文献

筛选
英文 中文
Diagnosis method of kiwifruit foliar diseases based on improved YOLOv4-tiny 基于改进YOLOv4-tiny的猕猴桃叶面病害诊断方法
2021 International Conference on Computer Engineering and Artificial Intelligence (ICCEAI) Pub Date : 2021-08-01 DOI: 10.1109/ICCEAI52939.2021.00058
Tianyu Ye, Zhaoming Wu, Shengqian Wang, Chengzhi Deng, Cong Tang
{"title":"Diagnosis method of kiwifruit foliar diseases based on improved YOLOv4-tiny","authors":"Tianyu Ye, Zhaoming Wu, Shengqian Wang, Chengzhi Deng, Cong Tang","doi":"10.1109/ICCEAI52939.2021.00058","DOIUrl":"https://doi.org/10.1109/ICCEAI52939.2021.00058","url":null,"abstract":"To solve the problem of slow diagnosis speed of kiwifruit foliar surface diseases and insufficient diagnosis ability of small target diseases, a lightweight network model based on YOLOv4-Tiny is proposed. Firstly, by introducing a depthwise separable convolution at the end of the backbone network, the number of parameters is reduced while the accuracy of diagnosis is guaranteed, and the training and diagnosis speed is improved. Secondly, SPP-Net is introduced in the Neck to realize the fusion of multiple receptive fields and the aggregation of multi-scale information, thereby improving the diagnostic accuracy of the model. Lastly, the multi-feature fusion FPN model is modified to improve the diagnosis ability of small target diseases, and then improve the diagnosis accuracy. The experimental results show that our method is superior to YOLOv4-Tiny on mAP@O.5, diagnosis speed, model size and small target disease diagnosis ability.","PeriodicalId":331409,"journal":{"name":"2021 International Conference on Computer Engineering and Artificial Intelligence (ICCEAI)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124924006","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 way of survival based on heuristic Dijkstra algorithm 基于启发式Dijkstra算法的生存方式
2021 International Conference on Computer Engineering and Artificial Intelligence (ICCEAI) Pub Date : 2021-08-01 DOI: 10.1109/ICCEAI52939.2021.00087
Zhang Haidong, Chen Qiuyu, Dou Yajie
{"title":"The way of survival based on heuristic Dijkstra algorithm","authors":"Zhang Haidong, Chen Qiuyu, Dou Yajie","doi":"10.1109/ICCEAI52939.2021.00087","DOIUrl":"https://doi.org/10.1109/ICCEAI52939.2021.00087","url":null,"abstract":"For the “LifeAfter” survival game problem, in order to make it smooth customs clearance, players need to meet multiple conditions, so the survival problem is abstracted into the path planning problem under multiple constraints. Aiming at this problem, we create A-D algorithm based on heuristic A * algorithm and Dijkstra algorithm. In order to reduce the complexity of computer calculation, we greatly improve the operation efficiency of the algorithm by the method of space exchange time. For the three problems in the topic, we propose three different benefit functions to optimize the global, avoid falling into the local optimal solution, guide the player under the constraints of multiple conditions, as far as possible to make the objective function value the largest (respectively: the least supply point (the sum of campfire point and food point), the path, the end point of satiation and comfort is the largest).","PeriodicalId":331409,"journal":{"name":"2021 International Conference on Computer Engineering and Artificial Intelligence (ICCEAI)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122828373","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
Effect of “Ying Wei Fang” on Vascular Endothelial Function in Patients with Different Syndromes of Type 2 Diabetes Mellitus 应胃方对2型糖尿病不同证型患者血管内皮功能的影响
2021 International Conference on Computer Engineering and Artificial Intelligence (ICCEAI) Pub Date : 2021-08-01 DOI: 10.1109/ICCEAI52939.2021.00095
Li Ruiyu, Li Yue, L. Xing, Li Meng
{"title":"Effect of “Ying Wei Fang” on Vascular Endothelial Function in Patients with Different Syndromes of Type 2 Diabetes Mellitus","authors":"Li Ruiyu, Li Yue, L. Xing, Li Meng","doi":"10.1109/ICCEAI52939.2021.00095","DOIUrl":"https://doi.org/10.1109/ICCEAI52939.2021.00095","url":null,"abstract":"Objective: To investigate the effects of “Yingwei Fang” on nitric oxide synthase (eNOS), endothelin-converting enzyme (ECE) and homocysteine (Hey) in patients with type 2 diabetes mellitus. Methods: 39 cases of type 2 diabetes mellitus with different syndromes were observed, including 14 cases of Yin deficiency heat, 10 cases of Qi and Yin deficiency and 15 cases of Yin and Yang deficiency. All patients took “Yingwei Fang” capsules orally, 5 capsules per time, 3 times a day. At the same time, they were combined with conventional treatment such as dialectical TCM dialectical theory of treatment and hypoglycemia. The changes of eNOS, ECE and Hcy were measured after 150 days of treatment and compared with those before treatment. RESULTs: After treatment, there were changes in $e$NOS, ECE and Hcy in patients with Yin deficiency, Qi and Yin deficiency and Yin and Yang deficiency, among which eNOS, ECE and Hcy were significantly improved (P<0.05). ECE and Hcy were significantly improved in both Qi and Yin deficiency (P<0.01). Conclusion: “Yingwei Fang” can significantly improve vascular endothelial function in patients with type 2 diabetes.","PeriodicalId":331409,"journal":{"name":"2021 International Conference on Computer Engineering and Artificial Intelligence (ICCEAI)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132827684","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
TripletGAN VeinNet: Palm Vein Recognition Based on Generative Adversarial Network and Triplet Loss 基于生成对抗网络和三重损失的手掌静脉识别
2021 International Conference on Computer Engineering and Artificial Intelligence (ICCEAI) Pub Date : 2021-08-01 DOI: 10.1109/ICCEAI52939.2021.00088
Aung Si Min Htet, H. Lee
{"title":"TripletGAN VeinNet: Palm Vein Recognition Based on Generative Adversarial Network and Triplet Loss","authors":"Aung Si Min Htet, H. Lee","doi":"10.1109/ICCEAI52939.2021.00088","DOIUrl":"https://doi.org/10.1109/ICCEAI52939.2021.00088","url":null,"abstract":"In recent years, palm vein recognition has obtained significant attention as its uniqueness, stable features, and high recognition rate. Although state-of-art deep learning methods can outperform several research domains, the lack of sufficiently large data for vein-based biometric recognition can suffer from generalization problems and degrades the model accuracy. Our approach trained Generative Adversarial Nets (GAN) with triplet loss for classification as an additional task. Lately, triplet networks are widely applied as it learns the latent space representation between neighbors and performs significantly higher accuracy even for insufficient data size. Moreover, in practical application, the quality of acquired vein images is low due to external factors and affects the recognition accuracy. To overcome this problem, we propose a CNN-based Encoder-Decoder network for vein segmentation to utilize the accuracy performance. Jerman enhancement filter is applied to enhance the vein ROI images for labeling the ground truth mask images for training the Encoder-Decoder network.","PeriodicalId":331409,"journal":{"name":"2021 International Conference on Computer Engineering and Artificial Intelligence (ICCEAI)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115393676","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
A Summary of the Latest Research on Knowledge Graph Technology 知识图谱技术最新研究综述
2021 International Conference on Computer Engineering and Artificial Intelligence (ICCEAI) Pub Date : 2021-08-01 DOI: 10.1109/ICCEAI52939.2021.00007
Y. Wu, Xue-feng Fu, Lichen Xu, Z. Jiang
{"title":"A Summary of the Latest Research on Knowledge Graph Technology","authors":"Y. Wu, Xue-feng Fu, Lichen Xu, Z. Jiang","doi":"10.1109/ICCEAI52939.2021.00007","DOIUrl":"https://doi.org/10.1109/ICCEAI52939.2021.00007","url":null,"abstract":"In recent years, with the in-depth development of cognitive intelligence technology, knowledge graph and its related technologies have also made breakthroughs, specifically reflected in the construction of knowledge graph, reasoning and computing technology. On the basis of a comprehensive description of the definition of knowledge graph and the discussion of the development history of knowledge graph technology, this paper summarizes their current scientific research progress around the two major technologies of knowledge representation learning and knowledge extraction in knowledge graph. This paper discriminates the advantages and disadvantages of the two technologies, and points out the direction for the follow-up research and improvement of the technology. Finally, the paper makes a summary and prospect of the future research direction of knowledge graph technology.","PeriodicalId":331409,"journal":{"name":"2021 International Conference on Computer Engineering and Artificial Intelligence (ICCEAI)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115417233","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
DAMVNet: Three-dimensional point cloud classification network based on dual attention mechanism and VLAD DAMVNet:基于双注意机制和VLAD的三维点云分类网络
2021 International Conference on Computer Engineering and Artificial Intelligence (ICCEAI) Pub Date : 2021-08-01 DOI: 10.1109/ICCEAI52939.2021.00014
Guodao Zhang, Xiaotian Pan, Li Xiao-nan, Zhang zhi-yong, Wei Wu, Ping-Kuo Chen
{"title":"DAMVNet: Three-dimensional point cloud classification network based on dual attention mechanism and VLAD","authors":"Guodao Zhang, Xiaotian Pan, Li Xiao-nan, Zhang zhi-yong, Wei Wu, Ping-Kuo Chen","doi":"10.1109/ICCEAI52939.2021.00014","DOIUrl":"https://doi.org/10.1109/ICCEAI52939.2021.00014","url":null,"abstract":"Aiming at the lack of effective use of contextual fine-grained local features in the existing deep learning-based 3D point cloud classification model, which leads to lower classification accuracy, a three-dimensional point cloud classification network based on dual attention mechanism and VLAD is proposed. Firstly, the local fine-grained features and global information of point cloud are mined by self-attention mechanism, and then the local geometric representation is learned by embedding graph attention mechanism in MLP layer. To take full advantage of the features, a multi-headed mechanism is used to aggregate different features from separate headers, and an effective key point descriptor is introduced to help identify the global geometry. Finally, the high-level semantic features of point clouds are obtained by locally aggregating vector VLAD layers. The experimental results show that the model achieves 92.45% accuracy on Mode1Net40 dataset.","PeriodicalId":331409,"journal":{"name":"2021 International Conference on Computer Engineering and Artificial Intelligence (ICCEAI)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123419791","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
Industrial object detection method based on improved CenterNet 基于改进CenterNet的工业目标检测方法
2021 International Conference on Computer Engineering and Artificial Intelligence (ICCEAI) Pub Date : 2021-08-01 DOI: 10.1109/ICCEAI52939.2021.00023
Cong Tang, Zhaoming Wu, Shengqian Wang, Chengzhi Deng, Linjie Luo
{"title":"Industrial object detection method based on improved CenterNet","authors":"Cong Tang, Zhaoming Wu, Shengqian Wang, Chengzhi Deng, Linjie Luo","doi":"10.1109/ICCEAI52939.2021.00023","DOIUrl":"https://doi.org/10.1109/ICCEAI52939.2021.00023","url":null,"abstract":"Aiming at the contradiction between accuracy and speed in industrial object detection, this paper proposes an industrial object detection method based on improved CenterNet. The improved method uses ResNet-50 as the Backbone to boost detection speed, and an upsampling layer is added to the feature processing network to improve detection accuracy. The expermient results show that the mAP of the improved method reaches 87.41 %, which is 3.44% higher than the CenterNet-Res101 method, and the detection speed reaches 31 FPS, which is 4 FPS faster than the CenterNet-Res101 method.","PeriodicalId":331409,"journal":{"name":"2021 International Conference on Computer Engineering and Artificial Intelligence (ICCEAI)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123009299","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: 2
An Improved Non-local Mean Filtering Algorithm Based on Medical Image Restoration 基于医学图像恢复的改进非局部均值滤波算法
2021 International Conference on Computer Engineering and Artificial Intelligence (ICCEAI) Pub Date : 2021-08-01 DOI: 10.1109/ICCEAI52939.2021.00008
Songjian Bao
{"title":"An Improved Non-local Mean Filtering Algorithm Based on Medical Image Restoration","authors":"Songjian Bao","doi":"10.1109/ICCEAI52939.2021.00008","DOIUrl":"https://doi.org/10.1109/ICCEAI52939.2021.00008","url":null,"abstract":"In the process of image imaging, replication, scanning, transmission and display, image degradation will inevitably occur, such as image blurring, noise interference, etc. In the field of medical image application, clear and high-quality images are needed. Therefore, medical image restoration is of great significance. In view of the fact that the current popular image restoration algorithms are less than ideal, this paper proposes an improved non-local mean filtering algorithm based on medical image restoration. This algorithm firstly adopts the norm LO gradient minimization restoration algorithm to restore the smooth part of the image, then adopts the wave-atom transformation to restore the detail part of the image, and finally adopts the improved non-local mean filtering to deal with the ringing effect and false edge generated by wave-atom transformation. The algorithm experiment was carried out on MATLAB R2009a platform. The experimental results show that the restoration algorithm has certain improvement in both subjective and objective effects of image restoration compared with the current popular image restoration algorithm.","PeriodicalId":331409,"journal":{"name":"2021 International Conference on Computer Engineering and Artificial Intelligence (ICCEAI)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123608193","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
Perioperative nursing experience of endometrial cancer patients with diabetes mellitus 子宫内膜癌合并糖尿病患者围手术期护理体会
2021 International Conference on Computer Engineering and Artificial Intelligence (ICCEAI) Pub Date : 2021-08-01 DOI: 10.1109/ICCEAI52939.2021.00103
Huiqing Hua, Lijuan Gao, Fengju Chen, Ting Sun, Lingling Wu
{"title":"Perioperative nursing experience of endometrial cancer patients with diabetes mellitus","authors":"Huiqing Hua, Lijuan Gao, Fengju Chen, Ting Sun, Lingling Wu","doi":"10.1109/ICCEAI52939.2021.00103","DOIUrl":"https://doi.org/10.1109/ICCEAI52939.2021.00103","url":null,"abstract":"Objective to explore the key points of perioperative nursing for patients with endometrial cancer complicated with diabetes mellitus. Method: In the perioperative nursing of 40 patients with endometrial cancer complicated with diabetes mellitus, we should strengthen blood glucose monitoring, diet control, incision management, pay attention to psychological nursing, and do a good job in discharge guidance. Result: Through the above nursing intervention, the patients recover quickly and have fewer complications. Conclusion: For the elderly patients with endometrial cancer and diabetes mellitus perioperative good and effective nursing intervention can promote patients to recover as soon as possible.","PeriodicalId":331409,"journal":{"name":"2021 International Conference on Computer Engineering and Artificial Intelligence (ICCEAI)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125774609","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
TQM-based Study on Teaching Quality Management of Online Teaching in Colleges and Universities
2021 International Conference on Computer Engineering and Artificial Intelligence (ICCEAI) Pub Date : 2021-08-01 DOI: 10.1109/ICCEAI52939.2021.00043
Lin Li
{"title":"TQM-based Study on Teaching Quality Management of Online Teaching in Colleges and Universities","authors":"Lin Li","doi":"10.1109/ICCEAI52939.2021.00043","DOIUrl":"https://doi.org/10.1109/ICCEAI52939.2021.00043","url":null,"abstract":"Under the guidance of the quality management concept of Total Quality Management (TQM) and combined with the actual situation of colleges and universities, this study discusses the concept of teaching quality management in colleges and universities, analyzes the key points of online teaching quality management in colleges and universities, and constructs the teaching quality management model of online teaching in colleges and universities on the basis of TQM.","PeriodicalId":331409,"journal":{"name":"2021 International Conference on Computer Engineering and Artificial Intelligence (ICCEAI)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127955651","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
首页 上一页 下一页 尾页
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整，为了账户安全，请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
请完成安全验证×
相关产品
×
本文献相关产品
联系我们：info@booksci.cn Book学术提供免费学术资源搜索服务，方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号：481959085
Book学术官方微信