... International Workshop on Pattern Recognition in NeuroImaging. International Workshop on Pattern Recognition in NeuroImaging最新文献_第3页

Surface defect detection algorithm for printing roller based on global contrast and edge gradient 基于全局对比度和边缘梯度的印刷辊表面缺陷检测算法

... International Workshop on Pattern Recognition in NeuroImaging. International Workshop on Pattern Recognition in NeuroImaging Pub Date : 2021-08-06 DOI: 10.1117/12.2604795

Bilong Li, Shaozhong Cao, Changfu Xu, Shuang Huang

引用次数: 0

Local Instrument with Geo-Tagging for Area Storm Surges (LIGTASS): a detection and monitoring system for marine vessels 具有区域风暴潮地理标记的本地仪器(LIGTASS):一种用于海洋船只的探测和监测系统

... International Workshop on Pattern Recognition in NeuroImaging. International Workshop on Pattern Recognition in NeuroImaging Pub Date : 2021-08-06 DOI: 10.1117/12.2605060

Jessie R. Balbin, C. Ostia, R. Fernando, J. Hernandez, Rafaela Yvonne Z. San Jose

{"title":"Local Instrument with Geo-Tagging for Area Storm Surges (LIGTASS): a detection and monitoring system for marine vessels","authors":"Jessie R. Balbin, C. Ostia, R. Fernando, J. Hernandez, Rafaela Yvonne Z. San Jose","doi":"10.1117/12.2605060","DOIUrl":"https://doi.org/10.1117/12.2605060","url":null,"abstract":"Ocean wave is inexhaustible energy resource. If harnessed efficiently, it could be an ideal source of energy. Though, the possibility is limitless, it comes with insurmountable dangers especially when surrounded by large bodies of water. This study focused on the design and construction of a Local Instrument with Geo-Tagging for Area Storm Surges (LIGTASS): A Detection and Monitoring System for Marine Vessels. Utilizing the multi-point absorber design, a type of Wave Energy Converter (WEC) in creating a device that detects and monitors storm surges. It aims to give aid to the needs of small-scale fishermen regarding the absence of weather information, security and power availability while being offshore of the coasts. The device measures three (3) parameters which are, (i) barometric Pressure or atmospheric pressure, (ii) wave Height and (iii) wind speed at the same time generating its own power from the ocean waves. It includes Geo-Tagging feature for device traceability and geo-mapping. Real-time data are stored via LTE to a cloud database using Arduino Uno modules. The results show that the parameters given above suffice to predict and detect storm surge occurrences based from the standards given by Department of Science and Technology-The Philippine Atmospheric, Geophysical and Astronomical Services Administration (DOST-PAGASA). The output data will not replace any DOST-PAGASA declarations. All data are subjected to T-test for statistical analysis. The data are only viable to the area of its deployment.","PeriodicalId":90079,"journal":{"name":"... International Workshop on Pattern Recognition in NeuroImaging. International Workshop on Pattern Recognition in NeuroImaging","volume":"30 1 1","pages":"1191309 - 1191309-5"},"PeriodicalIF":0.0,"publicationDate":"2021-08-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83544173","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

Facial expression recognition based on feature fusion 基于特征融合的面部表情识别

... International Workshop on Pattern Recognition in NeuroImaging. International Workshop on Pattern Recognition in NeuroImaging Pub Date : 2020-06-24 DOI: 10.1117/12.2574468

Jian Chen

引用次数: 1

3D pose reconstruction with multi-perspective and spatial confidence point group for jump analysis in figure skating 基于多视角和空间置信度点群的花样滑冰跳跃分析三维姿态重建

... International Workshop on Pattern Recognition in NeuroImaging. International Workshop on Pattern Recognition in NeuroImaging Pub Date : 2020-06-24 DOI: 10.1117/12.2574598

L. Tian, X. Cheng, M. Honda, T. Ikenaga

{"title":"3D pose reconstruction with multi-perspective and spatial confidence point group for jump analysis in figure skating","authors":"L. Tian, X. Cheng, M. Honda, T. Ikenaga","doi":"10.1117/12.2574598","DOIUrl":"https://doi.org/10.1117/12.2574598","url":null,"abstract":"Driven by recent computer vision applications, recovering 3D pose in the field of figure skating has become increasingly important. However, conventional works have suffered because of getting 3D information based on the corresponding 2D information directly or leaving the specificity of sports out of consideration. Issues such as restriction from self-occlusion, abnormal pose, limitation of venue and so on will result in poor results. Motivated by these problems, this paper proposes a multitask architecture based on a calibrated multi-camera system to facilitate jointly 3D jump pose of figure skater in the presence of the 2D Part Confidence Map. The proposals consist of three key components: Temporal smoothness and likelihood distribution based discrete probability points selection; Multi-perspective and combinations unification based large-scale venue 3D reconstruction; Spatial confidence point group and multiple constraints based human skeleton estimation. This work can be applied to 3D animated display and video motion capture of figure skating competition. The accuracy rate on the test sequences is 82.32% in body level and 92.96% in joint level.","PeriodicalId":90079,"journal":{"name":"... International Workshop on Pattern Recognition in NeuroImaging. International Workshop on Pattern Recognition in NeuroImaging","volume":"9 1","pages":"115260G - 115260G-10"},"PeriodicalIF":0.0,"publicationDate":"2020-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84470367","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: 3

Research of road scene object detection algorithm based on mobile platform 基于移动平台的道路场景目标检测算法研究

... International Workshop on Pattern Recognition in NeuroImaging. International Workshop on Pattern Recognition in NeuroImaging Pub Date : 2020-06-24 DOI: 10.1117/12.2574416

Yujia Chen, Xiaoning Liu, Chongwen Wang

{"title":"Research of road scene object detection algorithm based on mobile platform","authors":"Yujia Chen, Xiaoning Liu, Chongwen Wang","doi":"10.1117/12.2574416","DOIUrl":"https://doi.org/10.1117/12.2574416","url":null,"abstract":"There are many object detection methods in terms of object recognition based on traditional methods, but they are not sufficient to meet the demand for accuracy and speed in real-life scenarios. And compared with mobile platform, cloud service is also not conducive to the use in practical scenarios. Therefor we optimize the YOLO (You Only Look Once, a method for real-time detection of objects) algorithm through renormalization processing, build the Chinese road sign dataset and perform random affine transformation, random blur, and brightness transformation processing on the dataset to enhance the generalization ability of the final model. The parameters of the model are fine-tuned to reduce the period required to train the model and improve the performance of deep learning. Finally, the deep learning model of object detection will be transplanted to iOS mobile terminal to meet the requirements of real-time and accuracy in automatic driving scenarios. We identifie three types of road objects. The detection accuracy of pedestrians on road scenes reaches 75.9%, and the average detection accuracy of buses, cars, bicycles, and motorcycles is 72%. The detection accuracy of road signs is 69%. Total accuracy is 74.31%. The average detection rate of running tests on mobile phones is 12.5 frames per second.","PeriodicalId":90079,"journal":{"name":"... International Workshop on Pattern Recognition in NeuroImaging. International Workshop on Pattern Recognition in NeuroImaging","volume":"30 1","pages":"1152606 - 1152606-6"},"PeriodicalIF":0.0,"publicationDate":"2020-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85323455","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

Dictionary optimization and clustering for exemplar-based voice conversion 基于范例的语音转换的字典优化和聚类

... International Workshop on Pattern Recognition in NeuroImaging. International Workshop on Pattern Recognition in NeuroImaging Pub Date : 2020-06-24 DOI: 10.1117/12.2574413

Wei Sun, Yibiao Yu

引用次数: 1

Flight trajectory time and altitude prediction based on support vector and decision tree regressions 基于支持向量和决策树回归的飞行轨迹时间和高度预测

... International Workshop on Pattern Recognition in NeuroImaging. International Workshop on Pattern Recognition in NeuroImaging Pub Date : 2020-06-24 DOI: 10.1117/12.2574419

Yingchao Xiao, Yuanyuan Ma, Qiucheng Xu, Hui Ding

引用次数: 1

A classification method for rotor imbalance fault with ISFLA-SVM 基于ISFLA-SVM的转子不平衡故障分类方法

... International Workshop on Pattern Recognition in NeuroImaging. International Workshop on Pattern Recognition in NeuroImaging Pub Date : 2020-06-24 DOI: 10.1117/12.2574445

Lei You, Qiyi Han, Ying Liang, Jin Wang

引用次数: 1

Improved YOLO model with multi-feature fully convolutional network for object detection 基于多特征全卷积网络的目标检测改进YOLO模型

... International Workshop on Pattern Recognition in NeuroImaging. International Workshop on Pattern Recognition in NeuroImaging Pub Date : 2020-06-24 DOI: 10.1117/12.2574417

Yanbin Chen, Huai-Mu Wang, Zhuo Han

{"title":"Improved YOLO model with multi-feature fully convolutional network for object detection","authors":"Yanbin Chen, Huai-Mu Wang, Zhuo Han","doi":"10.1117/12.2574417","DOIUrl":"https://doi.org/10.1117/12.2574417","url":null,"abstract":"The main task of object detection is to identify and locate interested objects from still images or video sequences. It is one of the key tasks in the field of computer vision. However, the object usually has variable factors in brightness, shape, occlusion and so on, and is interfered by various and complex environmental factors, which makes the research opportunities and challenges of object detection algorithm coexist. In this paper, a main frame of object detection algorithm based on convolutional neural network is studied, which is based on regression. We propose a real-time object detection algorithm based on fully convolution network, which aims to solve the problems of low detection accuracy and poor location accuracy of objects in regression method. The innovation is that the proposed fully convolution network increases the detection flexibility of the model because it is not affected by the input scale. At the same time, we propose a multi feature fusion and multi border prediction strategy, which effectively improves the detection accuracy of small objects. In order to prove the effectiveness of the proposed algorithm, we use PASCAL VOC data set to carry out object detection experiments. In this paper, the accuracy of each object category and the average accuracy of all categories are calculated. Experiments show that the performance of the multi feature fusion algorithm based on the fully convolution network is better than that based on the regression idea such as YOLO, and more than 10% higher than that of the YOLO model.","PeriodicalId":90079,"journal":{"name":"... International Workshop on Pattern Recognition in NeuroImaging. International Workshop on Pattern Recognition in NeuroImaging","volume":"21 1","pages":"1152607 - 1152607-6"},"PeriodicalIF":0.0,"publicationDate":"2020-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89813267","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: 2

Intelligent deployment strategy based on genetic algorithm for software components in distributed system 分布式系统中基于遗传算法的软件组件智能部署策略

... International Workshop on Pattern Recognition in NeuroImaging. International Workshop on Pattern Recognition in NeuroImaging Pub Date : 2020-06-24 DOI: 10.1117/12.2574600

Hongzhen Zhang, Bo Jiang, Hong-xun Xu

引用次数: 1