Robust two-step image restoration with adaptive regularization parameter. - Ryan Wen Liu; Weihuang Wu; Maohan Liang; Tian Xu 001; Jingxian Liu (ICIIP, 2016)

Effective Alternating Direction Optimization Methods for Sparsity-Constrained Blind Image Deblurring. - Naixue Xiong; Ryan Wen Liu; Maohan Liang; Di Wu; Zhao Liu; Huisi Wu (Sensors, 2017)

Extraction of Hottest Shipping Routes: From Positioning Data to Intelligent Surveillance. - Ryan Wen Liu; Maohan Liang; Jiangtian Nie; Sahil Garg; Yang Zhang 025; Zehui Xiong (IRI, 2021)

Intelligent Data-Driven Vessel Trajectory Prediction in Marine Transportation Cyber-Physical System. - Ryan Wen Liu; Maohan Liang; Jiangtian Nie; Xianjun Deng; Zehui Xiong; Jiawen Kang 001; Helin Yang; Yang Zhang 025 (iThings/GreenCom/CPSCom/SmartData/Cybermatics, 2021)

An Unsupervised Learning Method with Convolutional Auto-Encoder for Vessel Trajectory Similarity Computation. - Maohan Liang; Ryan Wen Liu; Shichen Li; Zhe Xiao; Xin Liu; Feng Lu (CoRR, 2021)

MVFFNet: Multi-view feature fusion network for imbalanced ship classification. - Maohan Liang; Yang Zhan 007; Ryan Wen Liu (Pattern Recognit. Lett., 2021)

STMGCN: Mobile Edge Computing-Empowered Vessel Trajectory Prediction Using Spatio-Temporal Multigraph Convolutional Network. - Ryan Wen Liu; Maohan Liang; Jiangtian Nie; Yanli Yuan; Zehui Xiong; Han Yu 001; Nadra Guizani (IEEE Trans. Ind. Informatics, 2022)

Fine-Grained Vessel Traffic Flow Prediction With a Spatio-Temporal Multigraph Convolutional Network. - Maohan Liang; Ryan Wen Liu; Yang Zhan 007; Huanhuan Li 001; Fenghua Zhu; Fei-Yue Wang 001 (IEEE Trans. Intell. Transp. Syst., 2022)

Deep Learning-Powered Vessel Trajectory Prediction for Improving Smart Traffic Services in Maritime Internet of Things. - Ryan Wen Liu; Maohan Liang; Jiangtian Nie; Wei Yang Bryan Lim; Yang Zhang 025; Mohsen Guizani (IEEE Trans. Netw. Sci. Eng., 2022)

Deep Learning-Empowered Unsupervised Maritime Anomaly Detection. - Lingxuan Weng; Maohan Liang; Ruobin Gao; Zhong Shuo Chen (ICONIP (13), 2023)

Vessel Behavior Anomaly Detection Using Graph Attention Network. - Yuanzhe Zhang; Qiqiang Jin; Maohan Liang; Ruixin Ma; Ryan Wen Liu (ICONIP (5), 2023)

Deep learning-powered vessel traffic flow prediction with spatial-temporal attributes and similarity grouping. - Yan Li 110; Maohan Liang; Huanhuan Li 001; Zaili Yang; Liang Du 005; Zhongshuo Chen (Eng. Appl. Artif. Intell., 2023)

Benchmarking feed-forward randomized neural networks for vessel trajectory prediction. - Ruke Cheng; Maohan Liang; Huanhuan Li 001; Kum Fai Yuen (Comput. Electr. Eng., 2024)

A Survey of Distance-Based Vessel Trajectory Clustering: Data Pre-processing, Methodologies, Applications, and Experimental Evaluation. - Maohan Liang; Ryan Wen Liu; Ruobin Gao; Zhe Xiao; Xiaocai Zhang; Hua Wang (CoRR, 2024)

Spatio-temporal multi-graph transformer network for joint prediction of multiple vessel trajectories. - Ryan Wen Liu; Weixin Zheng; Maohan Liang (Eng. Appl. Artif. Intell., 2024)

Unsupervised maritime anomaly detection for intelligent situational awareness using AIS data. - Maohan Liang; Lingxuan Weng; Ruobin Gao; Yan Li 110; Liang Du 005 (Knowl. Based Syst., 2024)

PiracyAnalyzer: Spatial temporal patterns analysis of global piracy incidents. - Maohan Liang; Huanhuan Li 001; Ryan Wen Liu; Jasmine Siu Lee Lam; Zaili Yang (Reliab. Eng. Syst. Saf., 2024)

Advancements in Deep Learning Techniques for Time Series Forecasting in Maritime Applications: A Comprehensive Review. - Meng Wang; Xinyan Guo; Yanling She; Yang Zhou; Maohan Liang; Zhongshuo Chen (Inf., 2024)

Wave energy forecasting: A state-of-the-art survey and a comprehensive evaluation. - Ruobin Gao; Xiaocai Zhang; Maohan Liang; Ponnuthurai Nagaratnam Suganthan; Heng Dong (Appl. Soft Comput., 2025)

Big-data-driven vessel destination prediction for smart port management. - Jin Chen; Qiang Zhang; Maohan Liang; Chang Peng; Chen Chen (Eng. Appl. Artif. Intell., 2025)

Ship anomalous behavior detection based on interval prediction of multiple vessel trajectories. - Wentao Liu; Chen Chen; Yaowu Peng; Maohan Liang (Eng. Appl. Artif. Intell., 2025)

Deep-TCP: Multi-source data fusion for deep learning-powered tropical cyclone intensity prediction to enhance urban sustainability. - Shuailong Jiang; Maohan Liang; Chunzai Wang; Hanjie Fan; Yingying Ma (Inf. Fusion, 2025)

Exploring key factors for long-term vessel incident risk prediction. - Tianyi Chen; Hua Wang; Yutong Cai; Maohan Liang; Qiang Meng (Reliab. Eng. Syst. Saf., 2025)

Spatial-Frequency Fusion Network With Learnable Fractional Fourier Transform for Remote Sensing Imaging Enhancement. - Wenyu Xu; Maohan Liang; Yuxu Lu; Ruobin Gao; Dong Yang 003 (IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2025)

Underwater Acoustic Signal Denoising Algorithms: A Survey of the State of the Art. - Ruobin Gao; Maohan Liang; Heng Dong; Xuewen Luo; Ponnuthurai N. Suganthan (IEEE Trans. Instrum. Meas., 2025)

Integrating GPU-Accelerated for Fast Large-Scale Vessel Trajectories Visualization in Maritime IoT Systems. - Maohan Liang; Kezhong Liu; Ruobin Gao; Yan Li 110 (IEEE Trans. Intell. Transp. Syst., 2025)

Multi-Sensor Fusion-Driven Surface Vessel Identification and Tracking Using Unmanned Aerial Vehicles for Maritime Surveillance. - Chenjie Zhao; Mengwei Bao; Jinhao Liang; Maohan Liang; Ryan Wen Liu; Guangyao Pang (IEEE Trans. Consumer Electron., 2025)

Improving Maritime Data: A Machine Learning-Based Model for Missing Vessel Trajectories Reconstruction. - Jin Chen; Maohan Liang; Chang Peng; Jixin Zhang; Shengxu Huo (IEEE Trans. Veh. Technol., 2025)

Natural language processing and text mining in transportation: Current status, challenges, and future roadmap. - Xiaocai Zhang; Ruobin Gao; Zhe Xiao; Ke Wang; Tao Liu 016; Maohan Liang; Jianjia Zhang (Expert Syst. Appl., 2026)