Search Results for author: Jingxiang Qu

Found 5 papers, 3 papers with code

Deep Learning-Based Object Detection in Maritime Unmanned Aerial Vehicle Imagery: Review and Experimental Comparisons

no code implementations14 Nov 2023 Chenjie Zhao, Ryan Wen Liu, Jingxiang Qu, Ruobin Gao

To further promote the development of maritime UAV-based object detection, this paper provides a comprehensive review of challenges, relative methods, and UAV aerial datasets.

Object object-detection +1

Multi-Task Learning-Enabled Automatic Vessel Draft Reading for Intelligent Maritime Surveillance

no code implementations11 Oct 2023 Jingxiang Qu, Ryan Wen Liu, Chenjie Zhao, Yu Guo, Sendren Sheng-Dong Xu, Fenghua Zhu, Yisheng Lv

The accurate and efficient vessel draft reading (VDR) is an important component of intelligent maritime surveillance, which could be exploited to assist in judging whether the vessel is normally loaded or overloaded.

Depth Estimation Multi-Task Learning

SCANet: Self-Paced Semi-Curricular Attention Network for Non-Homogeneous Image Dehazing

1 code implementation17 Apr 2023 Yu Guo, Yuan Gao, Ryan Wen Liu, Yuxu Lu, Jingxiang Qu, Shengfeng He, Wenqi Ren

The presence of non-homogeneous haze can cause scene blurring, color distortion, low contrast, and other degradations that obscure texture details.

Image Dehazing

Asynchronous Trajectory Matching-Based Multimodal Maritime Data Fusion for Vessel Traffic Surveillance in Inland Waterways

2 code implementations22 Feb 2023 Yu Guo, Ryan Wen Liu, Jingxiang Qu, Yuxu Lu, Fenghua Zhu, Yisheng Lv

To further improve vessel traffic surveillance, it becomes necessary to fuse the AIS and video data to simultaneously capture the visual features, identity and dynamic information for the vessels of interest.

Position Vessel Detection

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