Search Results for author:
Found 17 papers, 6 papers with code
AoSRNet: All-in-One Scene Recovery Networks via Multi-knowledge Integration
Additionally, we suggest a multi-receptive field extraction module (MEM) to attenuate the loss of image texture details caused by GC nonlinear and OLS linear transformations.
Deep Learning-Based Object Detection in Maritime Unmanned Aerial Vehicle Imagery: Review and Experimental Comparisons
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.
Multi-Task Learning-Enabled Automatic Vessel Draft Reading for Intelligent Maritime Surveillance
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.
DADFNet: Dual Attention and Dual Frequency-Guided Dehazing Network for Video-Empowered Intelligent Transportation
To eliminate the influences of adverse weather conditions, we propose a dual attention and dual frequency-guided dehazing network (termed DADFNet) for real-time visibility enhancement.
SCANet: Self-Paced Semi-Curricular Attention Network for Non-Homogeneous Image Dehazing
The presence of non-homogeneous haze can cause scene blurring, color distortion, low contrast, and other degradations that obscure texture details.
Asynchronous Trajectory Matching-Based Multimodal Maritime Data Fusion for Vessel Traffic Surveillance in Inland Waterways
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.
STMGCN: Mobile Edge Computing-Empowered Vessel Trajectory Prediction Using Spatio-Temporal Multigraph Convolutional Network
—The revolutionary advances in machine learning and data mining techniques have contributed greatly to the rapid developments of maritime Internet of Things (IoT).
Rank-One Prior: Toward Real-Time Scene Recovery
To improve visual quality under different weather/imaging conditions, we propose a real-time light correction method to recover the degraded scenes in the cases of sandstorms, underwater, and haze.
An Unsupervised Learning Method with Convolutional Auto-Encoder for Vessel Trajectory Similarity Computation
Based on the massive vessel trajectories collected, the CAE can learn the low-dimensional representations of informative trajectory images in an unsupervised manner.
Low-Light Maritime Image Enhancement with Regularized Illumination Optimization and Deep Noise Suppression
To suppress the effect of unwanted noise on imaging performance, a deep learning-based blind denoising framework is further introduced to promote the visual quality of enhanced image.
Local Facial Makeup Transfer via Disentangled Representation
In this paper, we propose a novel unified adversarial disentangling network to further decompose face images into four independent components, i. e., personal identity, lips makeup style, eyes makeup style and face makeup style.
Similarity Grouping-Guided Neural Network Modeling for Maritime Time Series Prediction
Reliable and accurate prediction of time series plays a crucial role in maritime industry, such as economic investment, transportation planning, port planning and design, etc.
Directional Regularized Tensor Modeling for Video Rain Streaks Removal
Outdoor videos sometimes contain unexpected rain streaks due to the rainy weather, which bring negative effects on subsequent computer vision applications, e. g., video surveillance, object recognition and tracking, etc.
Variational Regularized Transmission Refinement for Image Dehazing
High-quality dehazing performance is highly dependent upon the accurate estimation of transmission map.
OCT segmentation: Integrating open parametric contour model of the retinal layers and shape constraint to the Mumford-Shah functional
The retinal layer boundary model consists of 9 open parametric contours representing the 9 retinal layers in OCT images.
A Robust Alternating Direction Method for Constrained Hybrid Variational Deblurring Model
In this work, a new constrained hybrid variational deblurring model is developed by combining the non-convex first- and second-order total variation regularizers.
