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NANXI WANG on Muck Rack

NANXI WANG

As seen in: Taylor & Francis Online, Academic Radiology

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Articles

Deep learning-based ship collision risk assessment under limited data: a Variational Autoencoder with Multilayer Perceptron and convolutional neural network approach

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By NANXI WANG, Chenyu Liu, Xinliang Zhou
| Taylor & Francis Online
ABSTRACT Driven by significant concerns about the risk of ship collisions within the maritime industry, this paper aims to propose an enhanced and intelligent method for assessing collision risks utilizing deep learning techniques. A novel research framework is introduced for assessing potential collision risk of ships entering monitored waterways by leveraging the Automatic Identification System (AIS) data, deep learning methods, and expert knowledge.
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[2509.09928] Fraud detection and risk assessment of online payment transactions on e-commerce platforms based on LLM and GCN frameworks

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By NANXI WANG, Xiaotong Zhu
| arXiv
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[2506.21927] A Deep Learning Algorithm Based on CNN-LSTM Framework for Predicting Cancer Drug Sales Volume

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By Yilin Yao, JungHua Lin, NANXI WANG
| arXiv
arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website. Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them. Have an idea for a project that will add value for arXiv's community? Learn more about arXivLabs.
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