International Conference on Informatics Engineering and Information Science最新文献

Multi-robot optimized sampling-base cooperative collision avoidance method in Lidar naviation 激光雷达导航中多机器人优化采样基协同避碰方法

International Conference on Informatics Engineering and Information Science Pub Date : 2022-10-26 DOI: 10.1117/12.2662007

Junlang Huang, Zhihua Zhang, Zhuoxin Wang, Zuguang Zhou, Yimin Zhou, C. Vong

引用次数: 0

High-speed measurement system for cord-rubber composites on conveyor belt based on machine vision 基于机器视觉的输送带绳胶复合材料高速测量系统

International Conference on Informatics Engineering and Information Science Pub Date : 2022-10-26 DOI: 10.1117/12.2662333

Peng Huang, Chenghao Liu, Xiaoying Yang, Dongwang Yi, Han Zhang

引用次数: 1

Design and analysis of swarm spherical robot based on machine vision 基于机器视觉的群球机器人设计与分析

International Conference on Informatics Engineering and Information Science Pub Date : 2022-10-26 DOI: 10.1117/12.2662217

Huang Peng, Yang Xiaoying, Liu Chenghao, Yi Dongwang, Cao Weihua, Mu Zongbo

引用次数: 0

Object recognition from on-the-road traffic data 从道路交通数据中识别物体

International Conference on Informatics Engineering and Information Science Pub Date : 2022-10-26 DOI: 10.1117/12.2662006

S. Muhammad, Qaisar Farooq, Chen Zuguo, Yimin Zhou

引用次数: 0

Damage detection of cylindrical structural steels based on finite element analysis 基于有限元分析的圆柱结构钢损伤检测

International Conference on Informatics Engineering and Information Science Pub Date : 2022-10-26 DOI: 10.1117/12.2662238

Ling Huang, Ziguo Xu, X. Y. Wei, G. Wang

引用次数: 0

Image saliency detection based on regional label fusion 基于区域标签融合的图像显著性检测

International Conference on Informatics Engineering and Information Science Pub Date : 2022-10-26 DOI: 10.1117/12.2659985

Pengfei Guo, Y. Wang, Lanjiang. Wang, Haitao Zhang

{"title":"Image saliency detection based on regional label fusion","authors":"Pengfei Guo, Y. Wang, Lanjiang. Wang, Haitao Zhang","doi":"10.1117/12.2659985","DOIUrl":"https://doi.org/10.1117/12.2659985","url":null,"abstract":"In this paper, an image saliency detection method based on regional label fusion is proposed to solve the problems with fuzzy boundaries, unclear profile, and less interior density commonly existing in the researches of salient region detection. The image is segmented by super pixel segmentation algorithm, then the spectral clustering is carried out for the super pixel region to reduce the number of regions, thereby the label set with the boundary information could be obtained. Next, three salient features of the image have been fused under conditional random field model to generate the coarse saliency map. Afterwards, regional label fusion method is operated, which organically fuses the boundary information into the coarse saliency map by using the salient mean value calculated with the label information as the regional salient features, moreover, together with adaptive threshold segmentation algorithm to acquire reconstructed saliency map. At last, accurate salient region detection is achieved by calculating with a tag indicating vector defined and reconstructed coarse saliency map. Experimental results show that the salient regions obtained by this algorithm display clearer boundary contours and that the density of salient regions has been greatly improved compared with the other six significant detection methods prevailed in recent years.","PeriodicalId":329761,"journal":{"name":"International Conference on Informatics Engineering and Information Science","volume":"31 10","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131859986","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

Garbage sorting system based on improved single shot multibox detector 基于改进型单镜头多盒探测器的垃圾分拣系统

International Conference on Informatics Engineering and Information Science Pub Date : 2022-10-26 DOI: 10.1117/12.2659971

Haomiao You, Limei Song, Jiankai Li, Xinjun Zhu

{"title":"Garbage sorting system based on improved single shot multibox detector","authors":"Haomiao You, Limei Song, Jiankai Li, Xinjun Zhu","doi":"10.1117/12.2659971","DOIUrl":"https://doi.org/10.1117/12.2659971","url":null,"abstract":"Garbage pollution is a very difficult problem in environmental governance. Due to the many sources of garbage pollution and a wide range of impacts, this problem is only slow to solve by human means. In order to improve the automation of garbage disposal, on the one hand, this paper proposes a garbage detection method based on CNN (convolutional neural network) using multi-layer feature processing. On the other hand, the detection algorithm is combined with an industrial robot to form a complete garbage sorting system. This paper uses the one-stage idea to first optimize the backbone structure to improve the extraction effect of shallow features. Then the attention module is introduced to make the network pay more attention to information that plays a key role in garbage detection. Finally, a multi-layer feature fusion method is used to combine the features of the shallow network with the features of the deep network to generate a fused feature map for use in target detection tasks. The experimental results show that the detection speed of the method proposed in this paper is 13.75% higher than that of SSD, and the garbage detection accuracy reaches 99.5%, which is better than the SSD detection algorithm. The garbage detection method proposed in this paper can quickly realize the precise positioning of garbage and complete automatic robot sorting.","PeriodicalId":329761,"journal":{"name":"International Conference on Informatics Engineering and Information Science","volume":"98 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134531529","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

Obstacle avoidance path planning of space manipulator based on improved RRT algorithm 基于改进RRT算法的空间机械臂避障路径规划

International Conference on Informatics Engineering and Information Science Pub Date : 2022-10-26 DOI: 10.1117/12.2660134

W. Bai, Xingzhi Xu

引用次数: 2