2022 IEEE 25th International Conference on Computational Science and Engineering (CSE)最新文献_第2页

Web-based Automatic Deep Learning Service Generation System by Ontology Technologies 基于本体技术的基于web的自动深度学习服务生成系统

2022 IEEE 25th International Conference on Computational Science and Engineering (CSE) Pub Date : 2022-12-01 DOI: 10.1109/CSE57773.2022.00019

Incheon Paik, Kungan Zeng, Munhan Bae

引用次数: 0

Message from the General Chairs: CSE 2022 总主席致辞:CSE 2022

2022 IEEE 25th International Conference on Computational Science and Engineering (CSE) Pub Date : 2022-12-01 DOI: 10.1109/cse57773.2022.00005

引用次数: 0

Design and Development of Operation Status Monitoring System for Large Glass Substrate Handling Robot 大型玻璃基板搬运机器人运行状态监控系统的设计与开发

2022 IEEE 25th International Conference on Computational Science and Engineering (CSE) Pub Date : 2022-12-01 DOI: 10.1109/CSE57773.2022.00020

Xinhe Pu, Xiaofang Yuan, Liangsen Li, Weiming Ji

{"title":"Design and Development of Operation Status Monitoring System for Large Glass Substrate Handling Robot","authors":"Xinhe Pu, Xiaofang Yuan, Liangsen Li, Weiming Ji","doi":"10.1109/CSE57773.2022.00020","DOIUrl":"https://doi.org/10.1109/CSE57773.2022.00020","url":null,"abstract":"Handling glass substrates is a component of the Flat Panel Display (FPD) industry's back-end process. Giant glass substrate handling robots have been developed in order to handle oversized, fragile, and delicate glass substrates. These robots have high precision, clean, smooth operation, and multi-constrained space requirements. In order to diagnose and maintain the handling robot, it is necessary to obtain accurate and rapid information regarding the defects. Currently, the display industry's actual needs for high-speed operation and a stable manufacturing line cannot be satisfied by manual diagnosis by maintenance engineers due to its inefficiency. This paper designed and developed a remote monitoring system based on the Web Internet platform. The system has the goal of monitoring and diagnosing the high-frequency operation, high reliability, and smooth operation of the large glass substrate handling robot. This system can monitor the running state of the robot in real time, quickly carry out fault alarm and diagnosis, and timely provide a fault warning function, ensuring the safe operation of the robot. It provides a link between companies that manufacture robots and companies that use them, which simplifies the diagnosis and repair of robot malfunctions.","PeriodicalId":165085,"journal":{"name":"2022 IEEE 25th International Conference on Computational Science and Engineering (CSE)","volume":"50 7","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132974032","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

Data-driven Prior for Pharmaceutical Snapshot Spectral Imaging 药物快照光谱成像的数据驱动先验

2022 IEEE 25th International Conference on Computational Science and Engineering (CSE) Pub Date : 2022-12-01 DOI: 10.1109/CSE57773.2022.00015

Xuesan Su, Jianxu Mao, Yaonan Wang, Yurong Chen, Hui Zhang

引用次数: 0

Dense 3D Face Reconstruction from a Single RGB Image 从单个RGB图像重建密集3D人脸

2022 IEEE 25th International Conference on Computational Science and Engineering (CSE) Pub Date : 2022-12-01 DOI: 10.1109/CSE57773.2022.00013

Jianxu Mao, Yifeng Zhang, Caiping Liu, Ziming Tao, Junfei Yi, Yaonan Wang

{"title":"Dense 3D Face Reconstruction from a Single RGB Image","authors":"Jianxu Mao, Yifeng Zhang, Caiping Liu, Ziming Tao, Junfei Yi, Yaonan Wang","doi":"10.1109/CSE57773.2022.00013","DOIUrl":"https://doi.org/10.1109/CSE57773.2022.00013","url":null,"abstract":"Monocular 3D face reconstruction is a computer vision problem of extraordinary difficulty. Restrictions of large poses and facial details(such as wrinkles, moles, beards etc.) are the common deficiencies of the most existing monocular 3D face reconstruction methods. To resolve the two defects, we propose an end-to-end system to provide 3D reconstructions of faces with details which express robustly under various backgrounds, pose rotations and occlusions. To obtain the facial detail informations, we leverage the image-to-image translation network (we call it p2p-net for short) to make pixel to pixel estimation from the input RGB image to depth map. This precise per-pixel estimation can provide depth value for facial details. And we use a procedure similar to image inpainting to recover the missing details. Simultaneously, for adapting pose rotation and resolving occlusions, we use CNNs to estimate a basic facial model based on 3D Morphable Model(3DMM), which can compensate the unseen facial part in the input image and decrease the deviation of final 3D model by fitting with the dense depth map. We propose an Identity Shape Loss function to enhance the basic facial model and we add a Multi-view Identity Loss that compare the features of the 3D face fusion and the ground truth from multi-view angles. The training data for p2p-net is from 3D scanning system, and we augment the dataset to a larger magnitude for a more generic training. Comparing to other state-of-the-art methods of 3D face reconstruction, we evaluate our method on in-the-wild face images. the qualitative and quantitative comparison show that our method performs both well on robustness and accuracy especially when facing non-frontal pose problems.","PeriodicalId":165085,"journal":{"name":"2022 IEEE 25th International Conference on Computational Science and Engineering (CSE)","volume":"83 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126322340","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