Dr. Yinghao Lin Profile

Dr. Yinghao Lin

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Publications (4)

Proceedings Article | 28 April 2023 Paper

A remote sensing work-flow recommendation algorithm based on logical structure

Xianyu Zuo, Yaohua Wu, Yang Liu, Yinghao Lin, Lei Zhang

Proceedings Volume 12626, 126261N (2023) https://doi.org/10.1117/12.2674447

KEYWORDS: Remote sensing, Process modeling, Data modeling, Data processing, Performance modeling, Matrices, Data conversion, Modeling, Design and modelling, Sensing systems

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With the development of remote sensing products towards the direction of civilianization and popularization, work-flow customization plays an important role in the production of remote sensing products. The traditional customized work-flow model has large time cost, complex operation and high requirements for professional knowledge. The work-flow recommendation system can improve the construction efficiency of remote sensing work-flow to some extent and assist users to design high-quality remote sensing work-flow models. However, most of the existing remote sensing work-flow modeling methods ignore the logical structure characteristics of the work-flow, leading to large errors in the calculation results of similarity. Difficult to make work-flow recommendations effectively. Therefore, this paper proposes a customized recommendation algorithm for remote sensing work-flow based on logical structure. By focusing on logical structure, the reliability of similarity calculation between work-flow is improved, so as to find similar work-flow to help users recommend the next modeling node. Firstly, the work-flow model needs to be preprocessed: the user converts the constructed work-flow model into a process structure tree by using Petri net workflow, and uses the path table generation algorithm based on logical structure to convert the model information into data information and store it in the database for subsequent data processing; Then the flow data in the flow tree set was converted into a path table according to certain rules, and then the longest common subsequence similarity of each data in the path table was calculated to obtain the similarity calculation results based on the logical structure characteristics, the most similar work-flow in the work-flow library is found and the recommendation is made for the user. The method proposed in this paper is evaluated experimentally on the real data set, in terms of recall, precision and F1-score, which shows that the method proposed in this paper can effectively improve the recommendation efficiency and meet the actual needs of users.

Proceedings Article | 28 April 2023 Paper

Differentially private discrete multi-attributed network releasing

Yinghao Lin, Yuye Wang, Shihao Zhao, Baojun Qiao

Proceedings Volume 12626, 126262P (2023) https://doi.org/10.1117/12.2674332

KEYWORDS: Social networks, Data modeling, Expectation maximization algorithms, Matrices, Data privacy, Connectors, Social network analysis, Semantics, Reflection, Internet

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Proceedings Article | 28 April 2023 Paper

Fusion attention-ASPP and context semantic for complex scene semantic segmentation

YingHao Lin, ShiHao Zhao, Kun Cai, BaoJun Qiao

Proceedings Volume 12626, 126260V (2023) https://doi.org/10.1117/12.2674281

KEYWORDS: Semantics, Image segmentation, Convolution, Remote sensing, Education and training, Data modeling, Matrices, Convolutional neural networks, Network architectures, Feature extraction

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Proceedings Article | 28 April 2023 Paper

Design and implementation of highly scalable IoT platform based on Netty

Xianyu Zuo, Bo Yuan, Shilong Li, Lanxue Dang, Yinghao Lin, Hongyu Han

Proceedings Volume 12626, 126262J (2023) https://doi.org/10.1117/12.2674380

KEYWORDS: Internet of things, Manufacturing, Design and modelling, Databases, Information operations, Data communications, Telecommunications, Safety, Manufacturing equipment, Instrument modeling

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