2020 International Conference on Culture-oriented Science & Technology (ICCST)最新文献_第3页

An interactive visual display system based on motion inertia parameters 基于运动惯量参数的交互式视觉显示系统

2020 International Conference on Culture-oriented Science & Technology (ICCST) Pub Date : 2020-10-01 DOI: 10.1109/ICCST50977.2020.00053

Yujian Jiang, Jia Wang, Kai Song

引用次数: 0

Research on Multimodal Algorithms for Multi-routes Planning Based on Niche Technique 基于小生境技术的多模式多路径规划算法研究

2020 International Conference on Culture-oriented Science & Technology (ICCST) Pub Date : 2020-10-01 DOI: 10.1109/ICCST50977.2020.00045

Hui Ren, Xiaochen Shen, X. Jia

引用次数: 1

An improved algorithm for deep learning YOLO network based on Xilinx ZYNQ FPGA 基于Xilinx ZYNQ FPGA的深度学习YOLO网络改进算法

2020 International Conference on Culture-oriented Science & Technology (ICCST) Pub Date : 2020-10-01 DOI: 10.1109/ICCST50977.2020.00092

Zheng Li, Jintao Wang

{"title":"An improved algorithm for deep learning YOLO network based on Xilinx ZYNQ FPGA","authors":"Zheng Li, Jintao Wang","doi":"10.1109/ICCST50977.2020.00092","DOIUrl":"https://doi.org/10.1109/ICCST50977.2020.00092","url":null,"abstract":"With the development of artificial intelligence, convolutional neural networks (CNN) have been widely used in image processing and other aspects due to their excellent performance. However, as a computationally intensive algorithm, CNN face huge challenges in the realization of mobile devices. FPGA have the advantages of high performance, reprogramming, and low power consumption, and have becoming suitable choices for CNN deployment. Compared with various CNN algorithms, the YOLO algorithm regards target detection as a regression problem. It is a one-step algorithm with fast execution speed and small amount of calculation. It is suitable for implementation on FPGA hardware platforms. This paper proposes an improved algorithm for deep learning YOLO network based on Xilinx ZYNQ FPGA. By optimizing the YOLO network model and fixed-point, etc., the problem of large computational of CNN and limited resources on FPGA chips is solved, and the parallelism of FPGA is used to accelerate the CNN. Experimental results show that the method proposed in this paper has greatly improved the operation rate while maintaining accuracy, and has important practical value in the realization of mobile terminals of CNN and real-time computing.","PeriodicalId":189809,"journal":{"name":"2020 International Conference on Culture-oriented Science & Technology (ICCST)","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122857110","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: 8

Research on Path-finding and Navigation Technology in VR Environment VR环境下的寻路导航技术研究

2020 International Conference on Culture-oriented Science & Technology (ICCST) Pub Date : 2020-10-01 DOI: 10.1109/ICCST50977.2020.00122

Pei Yi Yin, Chang Yuan Li

引用次数: 0

Question Answering system based on Knowledge Graph of Film Culture 基于电影文化知识图谱的问答系统

2020 International Conference on Culture-oriented Science & Technology (ICCST) Pub Date : 2020-10-01 DOI: 10.1109/ICCST50977.2020.00035

Qianjun Shuai, Cheng Zhang

引用次数: 3

Research on the coordination of stage lamps of cultural complex based on particle swarm optimization 基于粒子群优化的文化综合体舞台灯光协调研究

2020 International Conference on Culture-oriented Science & Technology (ICCST) Pub Date : 2020-10-01 DOI: 10.1109/ICCST50977.2020.00088

Hui Ren, Z. Ren

{"title":"Research on the coordination of stage lamps of cultural complex based on particle swarm optimization","authors":"Hui Ren, Z. Ren","doi":"10.1109/ICCST50977.2020.00088","DOIUrl":"https://doi.org/10.1109/ICCST50977.2020.00088","url":null,"abstract":"In a multi-functional small cultural service complex, it mainly includes different service functions such as performance, reading, exhibition, conference, folk custom, etc. The requirements of stage lamps’ position and brightness for each service function are different. On the premise of meeting the design requirements, to enable stage lamps to adjust brightness and reduce the consumption of energy optimally, a coordination scheme for stage lamps based on particle swarm optimization algorithm in a multi-functional small cultural service complex is proposed. It constructs the fitness function of the error of illuminance uniformity, energy consumption and visual uniformity. This article mainly studies the coordination of stage lamps in reading, exhibition and other scenes. It adopts LED lamps with automatic dimming and the idea of the small population in the particle swarm algorithm to improve the coordination and optimization of stage lamps. This paper uses MATLAB to simulate the two distribution schemes of random distribution and the improved layout of the particle swarm algorithm. The simulations show that the improved lamps coordination can further reduce energy and make the distribution of light brightness more reasonably.","PeriodicalId":189809,"journal":{"name":"2020 International Conference on Culture-oriented Science & Technology (ICCST)","volume":"75 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125832054","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

CNN-Based Medical Device Design for the Smart Pillbox With Face Recognition 基于cnn的智能药盒人脸识别医疗设备设计

2020 International Conference on Culture-oriented Science & Technology (ICCST) Pub Date : 2020-10-01 DOI: 10.1109/ICCST50977.2020.00125

Fan Wu, Yang-Cheng Lin, You-Hsun Wu

引用次数: 1

Research on Emotion Classification of Film and Television Scene Images Based on Different Salient Region 基于不同显著区域的影视场景图像情感分类研究

2020 International Conference on Culture-oriented Science & Technology (ICCST) Pub Date : 2020-10-01 DOI: 10.1109/ICCST50977.2020.00114

Zhibin Su, Bing Liu, Li-jing Zhang, Hui Ren

{"title":"Research on Emotion Classification of Film and Television Scene Images Based on Different Salient Region","authors":"Zhibin Su, Bing Liu, Li-jing Zhang, Hui Ren","doi":"10.1109/ICCST50977.2020.00114","DOIUrl":"https://doi.org/10.1109/ICCST50977.2020.00114","url":null,"abstract":"With the rapid development of intelligent image processing and computer vision, interpreting and extracting emotion information from images have become a hot research topic, especially the studies on film and television scene images with rich expressions and certain feelings from the aspect of audience. To investigate the distribution of emotions and its affect on the result of machine learning, this paper established the emotion classification models with different salient and non-salient regions based on self-built dataset from film and television works. Three salient extraction algorithms were used to the regional segmentation, and the color and texture features of each region were extracted. Emotion classification models were established based on SVM and RF algorithms respectively. Since features of the salient region could not cover all the information of the original image, the prediction accuracy of the unprocessed image was the highest. Nevertheless, when models made an error in the emotion prediction of the original image, the experimental results of salient region could get the correct answer under the certain circumstances. Through the analysis, the areas of interest can be used for emotion prediction to reduce the redundancy; however, to make it more accurate, the appropriate salient region extraction algorithm should be selected for different types of images and features. Our study provides data and theoretical guidance for image understanding and retrieval, and it has practical significance for more detailed classification based on the affective sensation.","PeriodicalId":189809,"journal":{"name":"2020 International Conference on Culture-oriented Science & Technology (ICCST)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130773843","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

Development Analysis of Three-Network Integration in the Era of 5G 5G时代三网融合发展分析

2020 International Conference on Culture-oriented Science & Technology (ICCST) Pub Date : 2020-10-01 DOI: 10.1109/ICCST50977.2020.00023

Jiaqi Zhao, Ming Yan, Jie Xu

引用次数: 0

Joint Depth Estimation and Semantic Segmentation with Adversarial Multi-task Network 基于对抗多任务网络的联合深度估计和语义分割

2020 International Conference on Culture-oriented Science & Technology (ICCST) Pub Date : 2020-10-01 DOI: 10.1109/ICCST50977.2020.00063

Hui Ren, Nan Gao, Jia Li

{"title":"Joint Depth Estimation and Semantic Segmentation with Adversarial Multi-task Network","authors":"Hui Ren, Nan Gao, Jia Li","doi":"10.1109/ICCST50977.2020.00063","DOIUrl":"https://doi.org/10.1109/ICCST50977.2020.00063","url":null,"abstract":"Some exiting works have explored the promotion between depth estimation and semantic segmentation. These works are usually based on convolutional neural networks, which extract compact features and map the relationship between input and output according to specific tasks. In this paper, we introduce a novel adversarial training strategy, that is, generator produces the semantic segmentation map and depth map, and then the discriminator can judge the authenticity of the synthesized color image, thereby supervising the output of the network during back propagation. We use the adversarial loss combined with the reconstruction loss function to supervise the model, and find that the adversarial loss function which is seen as a global supervision can further optimize the output. We use 200 color images from Kitti dataset with semantic segmentation ground truth as the training set, and train the network in an end-to-end manner. The experimental results show that the adversarial training method is well applied to the multi-task training combining semantic segmentation and depth estimation, and can further improve the quantitative performance of depth estimation.","PeriodicalId":189809,"journal":{"name":"2020 International Conference on Culture-oriented Science & Technology (ICCST)","volume":"91 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127678384","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