Proceedings of the 2019 3rd International Symposium on Computer Science and Intelligent Control最新文献_第6页

Real-time Head Detection for Automated Passenger Counting in Embedded Systems 嵌入式系统中乘客自动点票的实时头部检测

Proceedings of the 2019 3rd International Symposium on Computer Science and Intelligent Control Pub Date : 2019-09-25 DOI: 10.1145/3386164.3389086

Hyunduk Kim, Sang-Heon Lee, Myoung-Kyu Sohn

{"title":"Real-time Head Detection for Automated Passenger Counting in Embedded Systems","authors":"Hyunduk Kim, Sang-Heon Lee, Myoung-Kyu Sohn","doi":"10.1145/3386164.3389086","DOIUrl":"https://doi.org/10.1145/3386164.3389086","url":null,"abstract":"Head detection is a key problem for automated passenger counting systems. In recent decades, considerable effort has been expended to develop an accurate and reliable head detector. However, head detection is still a challenging task because of problems caused by variations in pose and occlusions. Recently, general object detection algorithms based on convolutional neural networks (CNNs), such as Faster R-CNN, SSD and YOLO, have been successful. However, these algorithms require the use of a Graphics Processing Unit (GPU) for real-time performance. In this study, we focused on developing real-time head detection in an embedded system. Starting with the Tiny-YOLOv3 network, we applied the following strategies to achieve real-time performance in a non-GPU environment. First, we reduced the input image size to 224x224. Second, we added an extra yolo layer to detect smaller heads. Third, we removed batch normalization. Finally, we conducted depthwise separable convolution rather than traditional convolution. Three public datasets, HollywoodHeads, SCUT_HEAD, and CrowdHuman, were exploited to train and test the proposed network, and Average Precision (AP) at Intersection over Unit (IoU) = 0.5 were used to evaluate the tests. Experimental results showed that the proposed network perform better and faster than Tiny-YOLOv3.","PeriodicalId":231209,"journal":{"name":"Proceedings of the 2019 3rd International Symposium on Computer Science and Intelligent Control","volume":"479 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123034303","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

IoT-aided Smart Lawnmower 物联网智能割草机

Proceedings of the 2019 3rd International Symposium on Computer Science and Intelligent Control Pub Date : 2019-09-25 DOI: 10.1145/3386164.3387298

Mutaz Ryalat, Mahmoud Alsherqatli, Hisham Elmoaqet

引用次数: 3

Research on Automatic Recognition of Homologous Plastic Seals 同源塑料封条的自动识别研究

Proceedings of the 2019 3rd International Symposium on Computer Science and Intelligent Control Pub Date : 2019-09-25 DOI: 10.1145/3386164.3389097

Qian Zhang, Weina Chen, Shunye Wang, Hongguang Hao

引用次数: 0

A Multi-Radar Track Fusion Methodology Based on Random Forest Regression 基于随机森林回归的多雷达航迹融合方法

Proceedings of the 2019 3rd International Symposium on Computer Science and Intelligent Control Pub Date : 2019-09-25 DOI: 10.1145/3386164.3389087

Zhanchun Gao, Zhiyang Zhang

{"title":"A Multi-Radar Track Fusion Methodology Based on Random Forest Regression","authors":"Zhanchun Gao, Zhiyang Zhang","doi":"10.1145/3386164.3389087","DOIUrl":"https://doi.org/10.1145/3386164.3389087","url":null,"abstract":"This paper introduces a multi-radar track fusion method based on random forest regression and provides an accurate and stable fusion track. The increasing number of aircraft will lead to congested routes, further leading to safety issues. Therefore, an effective track fusion method can accurately locate the aircraft, thereby ensuring the safety of the aircraft in the case of crowded routes. The basic idea of the method proposed in this paper is to select the radar data of a certain track of a certain day to train the model, and predict the position of the aircraft on the next day of the track through the trained model. As a traditional track fusion algorithm, the Kalman filtering has the problem of requiring accurate error estimation, insensitivity to noise, and long calculation time in the case of large data volume. The neural network method that compensates for these shortcomings also has the disadvantage of poor generalization ability in the case of a large amount of noise. The random forest regression model proposed in this paper can overcome the shortcomings of over-fitting in neural network, so it can achieve better prediction results. And through the real data test, the average error is 40m, compared with the neural network method, the result is increased by 50%.","PeriodicalId":231209,"journal":{"name":"Proceedings of the 2019 3rd International Symposium on Computer Science and Intelligent Control","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132487620","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

Hardware Scheduler Implementation based on Replicated Resource Architecture for Reconfigurable Systems 可重构系统中基于复制资源架构的硬件调度器实现

Proceedings of the 2019 3rd International Symposium on Computer Science and Intelligent Control Pub Date : 2019-09-25 DOI: 10.1145/3386164.3386175

I. Zagan, V. Gaitan

引用次数: 0

An Optimal Travel Route Recommender System for Tourists in Om Non Canal, Thailand 泰国欧侬运河游客最优旅游路线推荐系统

Proceedings of the 2019 3rd International Symposium on Computer Science and Intelligent Control Pub Date : 2019-09-25 DOI: 10.1145/3386164.3389103

P. Jomsri

引用次数: 2

Performance Measurements of Function as a Service Platforms 作为服务平台的功能性能测量

Proceedings of the 2019 3rd International Symposium on Computer Science and Intelligent Control Pub Date : 2019-09-25 DOI: 10.1145/3386164.3390516

Gellért István Hegyi, M. Maliosz, Csaba Simon

引用次数: 0

A Home Rehabilitation System Motivating Stroke Patients with Upper and/or Lower Limb Disability 一种促进上肢和/或下肢残疾中风患者的家庭康复系统

Proceedings of the 2019 3rd International Symposium on Computer Science and Intelligent Control Pub Date : 2019-09-25 DOI: 10.1145/3386164.3386168

Michael Opoku Agyeman, Ali Al-Mahmood, Igla Hoxha

引用次数: 6

LD-Parser: Leaf Detection Based Dependency Parsing Using BiLSTM and Attention Mechanism LD-Parser:基于叶子检测的依赖解析，使用BiLSTM和注意机制

Proceedings of the 2019 3rd International Symposium on Computer Science and Intelligent Control Pub Date : 2019-09-25 DOI: 10.1145/3386164.3389101

Wei Wen, Zhonglu Wang, Jianbo Liu, Chen Chen, Ni Li

引用次数: 0

Towards Flexible Process Automation: An Approach for Flexible Service Robot Adaptation and Allocation 面向柔性过程自动化:一种柔性服务机器人的自适应与分配方法

Proceedings of the 2019 3rd International Symposium on Computer Science and Intelligent Control Pub Date : 2019-09-25 DOI: 10.1145/3386164.3387292

Matthias Rollenhagen, M. Lutz, Nayabrasul Shaik, Kevin Andrews, S. Steinau, M. Reichert, C. Schlegel

引用次数: 2