Pub Date : 2021-08-01DOI: 10.1109/ICCEAI52939.2021.00058
Tianyu Ye, Zhaoming Wu, Shengqian Wang, Chengzhi Deng, Cong Tang
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.
{"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}
Pub Date : 2021-08-01DOI: 10.1109/ICCEAI52939.2021.00087
Zhang Haidong, Chen Qiuyu, Dou Yajie
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).
{"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}
Pub Date : 2021-08-01DOI: 10.1109/ICCEAI52939.2021.00095
Li Ruiyu, Li Yue, L. Xing, Li Meng
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.
{"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}
Pub Date : 2021-08-01DOI: 10.1109/ICCEAI52939.2021.00088
Aung Si Min Htet, H. Lee
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.
{"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}
Pub Date : 2021-08-01DOI: 10.1109/ICCEAI52939.2021.00007
Y. Wu, Xue-feng Fu, Lichen Xu, Z. Jiang
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.
{"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}
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.
{"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}
Pub Date : 2021-08-01DOI: 10.1109/ICCEAI52939.2021.00023
Cong Tang, Zhaoming Wu, Shengqian Wang, Chengzhi Deng, Linjie Luo
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.
{"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}
Pub Date : 2021-08-01DOI: 10.1109/ICCEAI52939.2021.00008
Songjian Bao
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.
{"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}
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.
{"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}
Pub Date : 2021-08-01DOI: 10.1109/ICCEAI52939.2021.00043
Lin Li
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.
{"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}
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