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Face Mask Recognition Based on Improved YOLOv7-Tiny 基于改进YOLOv7-Tiny的人脸识别
2023 4th International Seminar on Artificial Intelligence, Networking and Information Technology (AINIT) Pub Date : 2023-06-16 DOI: 10.1109/AINIT59027.2023.10212473
Benhai Yu, Mingjie Li
{"title":"Face Mask Recognition Based on Improved YOLOv7-Tiny","authors":"Benhai Yu, Mingjie Li","doi":"10.1109/AINIT59027.2023.10212473","DOIUrl":"https://doi.org/10.1109/AINIT59027.2023.10212473","url":null,"abstract":"A face mask recognition algorithm based on the improved YOLOv7-Tiny is proposed to address the current problems such as time-consuming and poor real-time performance of manual checking whether a mask is worn. Firstly, the Backbone of YOLOv7-Tiny is replaced by the MobileNetV3 network as a whole, making the structure more lightweight. Secondly, the edge loss function uses EIOU to improve the localization accuracy of face mask edges. Finally, the CBAM attention mechanism is added to improve the model detection performance. Experiments were conducted on the AIZOO dataset, and the improved YOLOv7-Tiny increased the mAP from 93.9% to 94.2% compared to the original algorithm, with a 28.3% decrease in the number of parameters and a 37.2% decrease in inference time. The experimental results show that the improved model is not only able to reduce the model size, but also improve the accuracy and speed of face mask detection, showing good mask recognition results.","PeriodicalId":276778,"journal":{"name":"2023 4th International Seminar on Artificial Intelligence, Networking and Information Technology (AINIT)","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123757383","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
Multi-Strategy Improved African Vulture Optimization Algorithm 改进的多策略非洲秃鹫优化算法
2023 4th International Seminar on Artificial Intelligence, Networking and Information Technology (AINIT) Pub Date : 2023-06-16 DOI: 10.1109/AINIT59027.2023.10212788
Dawei Ke, Cangsheng Yu
{"title":"Multi-Strategy Improved African Vulture Optimization Algorithm","authors":"Dawei Ke, Cangsheng Yu","doi":"10.1109/AINIT59027.2023.10212788","DOIUrl":"https://doi.org/10.1109/AINIT59027.2023.10212788","url":null,"abstract":"The problems of low convergence efficiency and easy to fall into local extremum in dealing with optimization problems of African vulture optimization algorithm, an improved multi-strategy African vulture algorithm (TSAVOA) combining Tent chaotic map, time-varying mechanism and adaptive hybrid strategy was proposed. The test results on typical unimodal and multimodal functions show that the improved African vulture algorithm compared with other algorithms, it is more excellent in various indicators and has better optimization effect.","PeriodicalId":276778,"journal":{"name":"2023 4th International Seminar on Artificial Intelligence, Networking and Information Technology (AINIT)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121923679","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 Robust OCT Image Retinal Layer Segmentation Method 一种鲁棒OCT图像视网膜层分割方法
2023 4th International Seminar on Artificial Intelligence, Networking and Information Technology (AINIT) Pub Date : 2023-06-16 DOI: 10.1109/AINIT59027.2023.10212846
Yi Gou, Renyong Zhang, Xiaoxia Zhou, Ke Li, Chenxi Li
{"title":"A Robust OCT Image Retinal Layer Segmentation Method","authors":"Yi Gou, Renyong Zhang, Xiaoxia Zhou, Ke Li, Chenxi Li","doi":"10.1109/AINIT59027.2023.10212846","DOIUrl":"https://doi.org/10.1109/AINIT59027.2023.10212846","url":null,"abstract":"Optical coherence tomography (OCT) images of the posterior eye are valuable clinical information, which can be used to more accurately diagnose and monitor retinal diseases by detecting changes in retinal layer thickness. In order to quantify OCT images and observe the thickness of each layer and its related information, this paper proposes a deep learning-based OCT image retinal layer segmentation method the MD-UNet model, which can assist in segmenting the different layers of OCT images. The model uses multi-channel feature extraction to improve the U-Net network and enhance the model's robustness. At the same time, the MD-UNet model finely extracts the structural features of each layer and uses the mIoU coefficient as the judgment index for layer structure edge optimization during fusion, thereby improving the overall and local segmentation accuracy and boundary precision. Through ablation experiments, it was demonstrated that the mIoU of the multi-channel structure and improved U-Net structure were improved by 3.05% and 0.34%, respectively. Comparative experimental results showed that this method outperformed other methods in terms of Dice coefficient and boundary error coefficient, demonstrating the effectiveness of this method.","PeriodicalId":276778,"journal":{"name":"2023 4th International Seminar on Artificial Intelligence, Networking and Information Technology (AINIT)","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114608175","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
Gesture Recognition Based on Flexible Data Glove Using Deep Learning Algorithms 基于深度学习算法的柔性数据手套手势识别
2023 4th International Seminar on Artificial Intelligence, Networking and Information Technology (AINIT) Pub Date : 2023-06-16 DOI: 10.1109/AINIT59027.2023.10212923
Kai Wang, Gang Zhao
{"title":"Gesture Recognition Based on Flexible Data Glove Using Deep Learning Algorithms","authors":"Kai Wang, Gang Zhao","doi":"10.1109/AINIT59027.2023.10212923","DOIUrl":"https://doi.org/10.1109/AINIT59027.2023.10212923","url":null,"abstract":"Gesture recognition based on wearable devices helps to build an intelligent human-computer interaction. However, the sensing units of current gesture acquisition devices are mostly rigid MEMS with poor user experience. Meanwhile, most existing studies directly stack gesture sensing data, ignoring the interaction of gesture signals within the same modal sensing channel and between different modal sensor channels in terms of spatiotemporal characteristics. To address the above problems, we use flexible data glove as gesture capture devices and propose a framework named self-attention temporal-spatial feature fusion for gesture recognition (STFGes) to recognize gestures by integrating multi-sensors data. In addition, we conduct comprehensive experiments to build a dataset that can be used for training and testing. The experimental results show that STFGes achieves 97.02% recognition accuracy for 10 dynamic daily Chinese Sign Language (CSL) and outperforms other methods.","PeriodicalId":276778,"journal":{"name":"2023 4th International Seminar on Artificial Intelligence, Networking and Information Technology (AINIT)","volume":"111 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128097139","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
Optimization Model and Algorithm for Port Shore Power Retrofitting Under “Double Carbon” Objective “双碳”目标下港口岸电改造优化模型与算法
2023 4th International Seminar on Artificial Intelligence, Networking and Information Technology (AINIT) Pub Date : 2023-06-16 DOI: 10.1109/AINIT59027.2023.10212733
Minglei Huang, Zipeng Du, Ziru Chen, Sixiao Guo
{"title":"Optimization Model and Algorithm for Port Shore Power Retrofitting Under “Double Carbon” Objective","authors":"Minglei Huang, Zipeng Du, Ziru Chen, Sixiao Guo","doi":"10.1109/AINIT59027.2023.10212733","DOIUrl":"https://doi.org/10.1109/AINIT59027.2023.10212733","url":null,"abstract":"As the global warming problem becomes more and more serious and the transformation of China's energy consumption structure continues to advance, the “double carbon” target has become a common choice for countries around the world to develop a low-carbon economy and cope with the climate crisis. In this context, the country has put forward the strategic deployment of peaking CO2 emissions by 2035 and striving to achieve carbon neutrality by 2060. As an important part of the transportation sector, the port industry is also facing great challenges, and we need to actively respond to the national policy and take the initiative to assume our own social responsibility. One of them is to accelerate the electrification process of existing berths and yards in port areas and promote the use of shore power technology. Based on this background, this paper studies the investment and operation mode of port shore power projects and related policy mechanisms from the perspective of port enterprises, and constructs an optimization model for port shore power renovation decision considering the demands of different interest subjects.","PeriodicalId":276778,"journal":{"name":"2023 4th International Seminar on Artificial Intelligence, Networking and Information Technology (AINIT)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130039402","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 of Transformer Protection Based on Joint Deep Learning 基于联合深度学习的变压器保护研究
2023 4th International Seminar on Artificial Intelligence, Networking and Information Technology (AINIT) Pub Date : 2023-06-16 DOI: 10.1109/AINIT59027.2023.10212577
Qiyue Huang, Yapeng Wang, S. Im
{"title":"Research of Transformer Protection Based on Joint Deep Learning","authors":"Qiyue Huang, Yapeng Wang, S. Im","doi":"10.1109/AINIT59027.2023.10212577","DOIUrl":"https://doi.org/10.1109/AINIT59027.2023.10212577","url":null,"abstract":"As the total electricity load and the proportion of renewable energy sources continue to rise in China, the power grid is experiencing an expansion in scale and an increasing complexity in its structure. As the most important equipment in the power system, the operation status of transformers directly affects the safety and stability of the system. Once a malfunction occurs, it will bring serious economic losses and harm. This paper proposes a transformer protection scheme based on joint deep learning method. Firstly, collect signals through the circuit breakers on both sides of the transformer to complete real-time data collection. Then, a gated recurrent neural network is used to achieve short-term and ultra short-term state recognition. In addition, self supervised learning task is added for joint training. Then the transformer fault diagnosis and protection are realized. Finally, using PSCAD software to construct a typical transformer model structure and conduct simulation verification using Jupyter Lab. The results show that the protection scheme has good performance in different sampling period lengths, noise interference, and data loss situations.","PeriodicalId":276778,"journal":{"name":"2023 4th International Seminar on Artificial Intelligence, Networking and Information Technology (AINIT)","volume":"46 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129054665","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 Multi-Label Recommendation Algorithm Based on Graph Attention and Sentiment Correction 基于图注意和情绪校正的多标签推荐算法
2023 4th International Seminar on Artificial Intelligence, Networking and Information Technology (AINIT) Pub Date : 2023-06-16 DOI: 10.1109/AINIT59027.2023.10212701
Ziyi Wu, Xindi Dai, Xiaoguang Wang, Yao Xiong, Shang Gao, Dainan Liu
{"title":"A Multi-Label Recommendation Algorithm Based on Graph Attention and Sentiment Correction","authors":"Ziyi Wu, Xindi Dai, Xiaoguang Wang, Yao Xiong, Shang Gao, Dainan Liu","doi":"10.1109/AINIT59027.2023.10212701","DOIUrl":"https://doi.org/10.1109/AINIT59027.2023.10212701","url":null,"abstract":"Traditional recommendation algorithms overlook the abundant information present in user feedback and are limited to the binary relationship between items and users. In contrast, this paper proposes an algorithm that takes advantage of item labels and user feedback to generate faster and more precise recommendation lists. The algorithm employs graph attention link prediction and sentiment analysis to calibrate parameters and enhance traditional recommendation algorithms by utilizing user information comprehensively. Empirical results on publicly available datasets indicate that the proposed algorithm outperforms both traditional and sentiment-uncorrected recommendation algorithms in terms of accuracy.","PeriodicalId":276778,"journal":{"name":"2023 4th International Seminar on Artificial Intelligence, Networking and Information Technology (AINIT)","volume":"55 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127586851","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
Optimized Deep Learning Model for Pose and Expression Invariant Face Recognition in an IoT-Cloud Environment 物联网云环境下姿态和表情不变人脸识别的优化深度学习模型
2023 4th International Seminar on Artificial Intelligence, Networking and Information Technology (AINIT) Pub Date : 2023-06-16 DOI: 10.1109/AINIT59027.2023.10212898
Alsulaiman Abdulaziz, Al-Jonaid Amjad Mohammed Ahmed, Obad Abdullah Yousef Rabea, Jinliang Li
{"title":"Optimized Deep Learning Model for Pose and Expression Invariant Face Recognition in an IoT-Cloud Environment","authors":"Alsulaiman Abdulaziz, Al-Jonaid Amjad Mohammed Ahmed, Obad Abdullah Yousef Rabea, Jinliang Li","doi":"10.1109/AINIT59027.2023.10212898","DOIUrl":"https://doi.org/10.1109/AINIT59027.2023.10212898","url":null,"abstract":"Face recognition from massive data in Internet-of-Things (IoT)-cloud environments is challenging with limitations in learning the pose and facial expression variations. An intelligent Pose and Expression Invariant Face Recognition Model (PEIFRM) is developed in this paper by extracting the local features of face pose and expression variations using Temporal Stacked Convolutional Denoising Autoencoder (TSCDAE) and Optimized Siamese Convolutional Ladder Networks (OSCLN) for recognition. TSCDAE acquires the local informative features of persons' facial pose and expression variations through different color components. OSCLN is an integration of Siamese neural networks (SNN), semi-supervised ladder form of convolutional neural networks (CNN) and Artificial Lizard Search Optimization (ALSO) to improve the training speed and reduce the error rate with local and global feature fusion to improve the recognition accuracy. Experimental results comparisons showed that the proposed PEIFRM model achieved 98.95% and 99.75% accuracies for LFW and ORL datasets, respectively.","PeriodicalId":276778,"journal":{"name":"2023 4th International Seminar on Artificial Intelligence, Networking and Information Technology (AINIT)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127194344","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
Analysis and Research on Intelligent Liquid Cargo Washing System Platform 智能液货洗涤系统平台的分析与研究
2023 4th International Seminar on Artificial Intelligence, Networking and Information Technology (AINIT) Pub Date : 2023-06-16 DOI: 10.1109/AINIT59027.2023.10212826
Fengran Chen
{"title":"Analysis and Research on Intelligent Liquid Cargo Washing System Platform","authors":"Fengran Chen","doi":"10.1109/AINIT59027.2023.10212826","DOIUrl":"https://doi.org/10.1109/AINIT59027.2023.10212826","url":null,"abstract":"In view of the problem that the software and hardware platforms of the current intelligent liquid cargo tank washing system cannot reach the closed-loop intelligent system mode, two kinds of chemical tanker tank washing systems are proposed, namely special chemical tanker tank washing system and general chemical tanker tank washing system. Special tank washing system is used in chemical transport ships with single chemical type and known physical and chemical properties. General purpose chemical tanker is usually used to transport more than two kinds of chemicals. The physical and chemical characteristics of each chemical are quite different. Before cleaning, the characteristics of the transported chemical must be analyzed. The proposed two kinds of tank washing systems can effectively improve the automatic intelligent cleaning of chemical tanker tank washing system at the present stage and provide a certain theoretical basis for the subsequent intelligent tank washing research.","PeriodicalId":276778,"journal":{"name":"2023 4th International Seminar on Artificial Intelligence, Networking and Information Technology (AINIT)","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127764821","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
DDoS attack detection method based on One-Hot coding and improved ResNet18 基于One-Hot编码和改进的ResNet18的DDoS攻击检测方法
2023 4th International Seminar on Artificial Intelligence, Networking and Information Technology (AINIT) Pub Date : 2023-06-16 DOI: 10.1109/AINIT59027.2023.10210725
Hanlin Lu, Beining Ying, Xujun Che, Zhaoning Jin, Mingxuan Wang, Shuhui Wu
{"title":"DDoS attack detection method based on One-Hot coding and improved ResNet18","authors":"Hanlin Lu, Beining Ying, Xujun Che, Zhaoning Jin, Mingxuan Wang, Shuhui Wu","doi":"10.1109/AINIT59027.2023.10210725","DOIUrl":"https://doi.org/10.1109/AINIT59027.2023.10210725","url":null,"abstract":"DDoS attack is easy to implement, concealed, and destructive. It has been a serious threat to network security. This paper chooses CIC-DDoS2019 as the dataset, removes the invalid redundant features and abnormal data from the dataset through data preprocessing, reconstructs the preprocessed network traffic data using One-Hot encoding, and finally selects the improved ResNet18 as the classifier to detect DDoS attacks. The experimental results show that the method can convert the network traffic data into binary images efficiently and improve the detection accuracy of ResNet18 to 98%.","PeriodicalId":276778,"journal":{"name":"2023 4th International Seminar on Artificial Intelligence, Networking and Information Technology (AINIT)","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133437505","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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