International Conference on Algorithm, Imaging Processing and Machine Vision (AIPMV 2023)最新文献_第2页

Research on automatic identification algorithm of invoice information 发票信息自动识别算法研究

International Conference on Algorithm, Imaging Processing and Machine Vision (AIPMV 2023) Pub Date : 2024-01-09 DOI: 10.1117/12.3014488

Liangyu Jiao, Hui Li

引用次数: 0

A music generation model based on Bi-LSTM 基于 Bi-LSTM 的音乐生成模型

International Conference on Algorithm, Imaging Processing and Machine Vision (AIPMV 2023) Pub Date : 2024-01-09 DOI: 10.1117/12.3014368

yong bai

引用次数: 0

Application analysis of three-dimensional laser scanning technology in the protection of dong drum tower in Sanjiang county 三维激光扫描技术在三江县东鼓楼保护中的应用分析

International Conference on Algorithm, Imaging Processing and Machine Vision (AIPMV 2023) Pub Date : 2024-01-09 DOI: 10.1117/12.3014534

Bin Huang

{"title":"Application analysis of three-dimensional laser scanning technology in the protection of dong drum tower in Sanjiang county","authors":"Bin Huang","doi":"10.1117/12.3014534","DOIUrl":"https://doi.org/10.1117/12.3014534","url":null,"abstract":"The three-dimensional laser scanning technology is a non-contact measurement of objects by using a three-dimensional scanner. It is a new surveying and mapping technology, also known as real-life replication technology. This technology can completely reconstruct the surface of the scanned object through the 360-degree rotation of the laser emitter. The accuracy of point cloud data is very high. Each three-dimensional data in the laser point cloud is the real three-dimensional data X, Y, and Z coordinates of the building target, which makes the post-processing data true and reliable, and its accuracy reaches 3mm ~ 6mm. The working principle of this technology is through reverse three-dimensional data acquisition and model reconstruction, on-site photography, texture mapping for the later period, can truly achieve 1 : 1 physical restoration, and then quickly reconstruct the three-dimensional model of the building, so as to obtain the building point, line, surface, body and other mapping data. Three-dimensional laser scanning technology has played a huge advantage in the reconstruction and protection of wooden structure drum tower.","PeriodicalId":516634,"journal":{"name":"International Conference on Algorithm, Imaging Processing and Machine Vision (AIPMV 2023)","volume":" 32","pages":"129691S - 129691S-8"},"PeriodicalIF":0.0,"publicationDate":"2024-01-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139640393","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

Coal gangue sorting based on deep learning 基于深度学习的煤矸石分拣

International Conference on Algorithm, Imaging Processing and Machine Vision (AIPMV 2023) Pub Date : 2024-01-09 DOI: 10.1117/12.3014357

Panliang Yang, Bin Zhu, Lianquan Ji, Peng Nie

引用次数: 0

Anti aliasing algorithm based on sub aperture stitching 基于子光圈拼接的抗混叠算法

International Conference on Algorithm, Imaging Processing and Machine Vision (AIPMV 2023) Pub Date : 2024-01-09 DOI: 10.1117/12.3014409

Dekun Li

引用次数: 0

Improved YOLOv5s recognition of cotton top buds with fusion of attention and feature weighting 融合注意力和特征权重，提高 YOLOv5s 对棉花顶芽的识别能力

International Conference on Algorithm, Imaging Processing and Machine Vision (AIPMV 2023) Pub Date : 2024-01-09 DOI: 10.1117/12.3014605

Lei Yin, Jian Wu, Qikong Liu, Wenxiong Wu

{"title":"Improved YOLOv5s recognition of cotton top buds with fusion of attention and feature weighting","authors":"Lei Yin, Jian Wu, Qikong Liu, Wenxiong Wu","doi":"10.1117/12.3014605","DOIUrl":"https://doi.org/10.1117/12.3014605","url":null,"abstract":"In order to improve the accuracy and real-time performance of cotton top bud recognition, an improved YOLOv5s target real-time detection model is proposed. First, the SE module and the CBAM module in the attention mechanism are added to optimize the weight ratio of channel attention and spatial attention to improve accuracy; then the BiFPN structure of bidirectional weighted features is introduced to strengthen the fusion between high-level features and low-level features; finally, a new bounding box regression loss function EIoU is used for ablation experiments, and more position information of cotton buds can be obtained by reducing the bounding box loss. The experimental results show that, by applying the improved algorithm in the identification of cotton top buds, compared with the original YOLOv5s model, the accuracy of the C3SE-4l+BiFPN+EIoU model has increased by 7.9%, the recall rate has increased by 2.8%, and the average precision an increase of 5.7%. These improvements and optimizations provide a new idea and method, which can provide a more efficient solution for the identification of cotton top buds.","PeriodicalId":516634,"journal":{"name":"International Conference on Algorithm, Imaging Processing and Machine Vision (AIPMV 2023)","volume":"48 3","pages":"1296928 - 1296928-6"},"PeriodicalIF":0.0,"publicationDate":"2024-01-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140511442","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

Moisture detection of oil-immersed bushing insulation based on color level analysis 基于色度分析的油浸套管绝缘层湿度检测

International Conference on Algorithm, Imaging Processing and Machine Vision (AIPMV 2023) Pub Date : 2024-01-09 DOI: 10.1117/12.3014683

Hongmin Ren, Denan Wang, Danni Duan

{"title":"Moisture detection of oil-immersed bushing insulation based on color level analysis","authors":"Hongmin Ren, Denan Wang, Danni Duan","doi":"10.1117/12.3014683","DOIUrl":"https://doi.org/10.1117/12.3014683","url":null,"abstract":"The operational level and service life of oil-immersed bushings are related to the moisture content in their cellulosic insulation layers. The authors proposed a novel method based on Taylor series modeling and grey relational analysis to assess the moisture content in the cellulosic insulation of oil-immersed bushings. Unlike conventional methods relying solely on frequency domain spectroscopy (FDS) data from certain frequency ranges, this method uses Taylor series to model the full spectrum and extracts a set of moisture-related feature parameters, thus avoiding dependence on specific measurement points or ranges. To establish the relationship between feature parameters and moisture levels, a database was constructed in this study. Grey relational analysis was used to propose an alternative method for assessing the moisture in bushing cellulosic insulation. Results show the average relative error between the estimated and measured moisture was less than 15.7%. Overall, the proposed method in this study provides an effective approach for assessing the moisture in the cellulosic insulation of oil-immersed bushings.","PeriodicalId":516634,"journal":{"name":"International Conference on Algorithm, Imaging Processing and Machine Vision (AIPMV 2023)","volume":"62 1","pages":"129692Q - 129692Q-6"},"PeriodicalIF":0.0,"publicationDate":"2024-01-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140511314","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

Concrete crack identification and detection method based on improved CNN and DoG operator 基于改进型 CNN 和 DoG 算子的混凝土裂缝识别和检测方法

International Conference on Algorithm, Imaging Processing and Machine Vision (AIPMV 2023) Pub Date : 2024-01-09 DOI: 10.1117/12.3014461

Haohua Luo, Yulun Wu, Yaoyang Liang, Jinshuai Ren, Zhiming Wang, Yilu Huang

{"title":"Concrete crack identification and detection method based on improved CNN and DoG operator","authors":"Haohua Luo, Yulun Wu, Yaoyang Liang, Jinshuai Ren, Zhiming Wang, Yilu Huang","doi":"10.1117/12.3014461","DOIUrl":"https://doi.org/10.1117/12.3014461","url":null,"abstract":"Concrete will produce cracks under the long-term action of loads and affect the building safety, due to the unsatisfactory accuracy and efficiency of manual detection of concrete cracks, a concrete crack recognition and detection method based on improved CNN and DoG operator is proposed. Firstly, the recognition ability is trained by CNN to locate the valuable images from the image dataset, and then the locating crack images are greyscaled, denoised using bilateral filtering method, considering that the filtering will make the image edges blurred, the DoG operator is used to detect the completeness of the edges, and then the image is binary transformed by selecting thresholds through the one-dimensional Otus segmentation method, and the binary map is opened by the open operation, to fill in the broken parts within the cracks and protect the crack edges, and finally the length, width, and rotation angle of the crack are calculated by mapping the complete straight lines present in the crack through Hough space. The experimental results show that the method can accurately identify and detect crack features of different shapes with superior detection accuracy.","PeriodicalId":516634,"journal":{"name":"International Conference on Algorithm, Imaging Processing and Machine Vision (AIPMV 2023)","volume":"44 5","pages":"1296925 - 1296925-5"},"PeriodicalIF":0.0,"publicationDate":"2024-01-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140511333","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

Energy consumption and carbon emission measurement online detection method based on hybrid particle swarm optimization algorithm 基于混合粒子群优化算法的能耗和碳排放测量在线检测方法

International Conference on Algorithm, Imaging Processing and Machine Vision (AIPMV 2023) Pub Date : 2024-01-09 DOI: 10.1117/12.3014377

Tianyi Zhang, Huaiying Shang, Angang Zheng

{"title":"Energy consumption and carbon emission measurement online detection method based on hybrid particle swarm optimization algorithm","authors":"Tianyi Zhang, Huaiying Shang, Angang Zheng","doi":"10.1117/12.3014377","DOIUrl":"https://doi.org/10.1117/12.3014377","url":null,"abstract":"The detection data of energy consumption and carbon emissions may be affected by equipment failure, sensor error, incomplete data collection and other factors, resulting in low detection accuracy. Based on this, an online detection method of energy consumption and carbon emissions measurement based on hybrid particle swarm optimization algorithm is proposed. Analyze the measurement principles of energy consumption and carbon emissions. On this basis, collect the measurement data of energy consumption and carbon emissions in real time, use semi-supervised learning to extract the measurement operation data, calculate the Angle between the newly generated optimization solution and the reference direction vector, and use it as the attribute space of particle update, and assign all optimization target values, and use the hybrid particle swarm optimization algorithm. The on-line measurement process based on hybrid particle swarm optimization algorithm is completed. The experimental results show that the proposed method has advantages in all aspects of performance index, AUC value is higher than 0.9, detection time is lower than 8s.","PeriodicalId":516634,"journal":{"name":"International Conference on Algorithm, Imaging Processing and Machine Vision (AIPMV 2023)","volume":"164 2","pages":"129690N - 129690N-6"},"PeriodicalIF":0.0,"publicationDate":"2024-01-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140511916","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 obstacle distance measurement method of UAV based on image processing technology 基于图像处理技术的无人机障碍物距离测量方法研究

International Conference on Algorithm, Imaging Processing and Machine Vision (AIPMV 2023) Pub Date : 2024-01-09 DOI: 10.1117/12.3014383

mingxia Lin

{"title":"Research on obstacle distance measurement method of UAV based on image processing technology","authors":"mingxia Lin","doi":"10.1117/12.3014383","DOIUrl":"https://doi.org/10.1117/12.3014383","url":null,"abstract":"In order to understand the obstacle distance measurement method of UAV, a research on obstacle distance measurement method of UAV based on image processing technology is proposed. This paper proposes an obstacle detection algorithm based on edge extraction. The outline of the obstacle can be obtained by extracting the edge features in the image, and the size, shape and position of the obstacle can be obtained by using a rectangle to frame the outline. Then the distance of the obstacle can be extracted from the contour of the obstacle by using the depth map generated by the binocular camera. The millimeter wave radar in front is used to fuse ranging with the central area of binocular camera image to improve the update frequency of obstacle distance. Finally, the effectiveness of the obstacle avoidance control strategy is verified by the obstacle avoidance flight test, and the UAV can choose the optimal obstacle avoidance direction and successfully bypass when encountering obstacles. The comparison of obstacle avoidance results shows that the obstacle avoidance method in this paper is advanced and has certain engineering application value.","PeriodicalId":516634,"journal":{"name":"International Conference on Algorithm, Imaging Processing and Machine Vision (AIPMV 2023)","volume":"18 3","pages":"1296912 - 1296912-6"},"PeriodicalIF":0.0,"publicationDate":"2024-01-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140512105","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