Xiufen Ye
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View article: Advancing monocular depth estimation by integrating underwater optical imaging priors into transformer-based network
Advancing monocular depth estimation by integrating underwater optical imaging priors into transformer-based network Open
Underwater monocular depth estimation is highly valuable for resource-constrained miniature autonomous robots due to its compact installation and low cost. However, underwater images are often degraded by light scattering and absorption, r…
View article: Water-exit dynamics and system identification for a hybrid aerial underwater vehicle
Water-exit dynamics and system identification for a hybrid aerial underwater vehicle Open
Affected by the sudden change of medium, the water-exit process of the hybrid aerial underwater vehicles (HAUVs) brings tremendous challenges to the stable control of these special vehicles, such as complex fluid dynamics and modeling diff…
View article: TFCNet: A Hybrid Architecture for Multi-Task Restoration of Complex Underwater Optical Images
TFCNet: A Hybrid Architecture for Multi-Task Restoration of Complex Underwater Optical Images Open
Underwater optical images are crucial in marine exploration. However, capturing these images directly often results in color distortion, noise, blurring, and other undesirable effects, all of which originate from the unique physical and ch…
View article: An Improved Real-Time LOS-Based Model Predictive Control for the Semi-Submersible Offshore Platform Under Ocean Disturbances
An Improved Real-Time LOS-Based Model Predictive Control for the Semi-Submersible Offshore Platform Under Ocean Disturbances Open
To enhance the autonomy of semi-submersibles, a Model Predictive Control (MPC) strategy was proposed based on real-time Line-of-Sight (LOS) to address the issue of thruster saturation. By identifying parameters using experimental data from…
View article: Correction: Chen et al. Design of a Sliding Mode Controller for Lateral Motion Control of a Supercavitating Vehicle Based on a Radial Basis Function Neural Network Observer. J. Mar. Sci. Eng. 2025, 13, 418
Correction: Chen et al. Design of a Sliding Mode Controller for Lateral Motion Control of a Supercavitating Vehicle Based on a Radial Basis Function Neural Network Observer. J. Mar. Sci. Eng. 2025, 13, 418 Open
There was an error in the original paper [...]
View article: Design of a Sliding Mode Controller for Lateral Motion Control of a Supercavitating Vehicle Based on a Radial Basis Function Neural Network Observer
Design of a Sliding Mode Controller for Lateral Motion Control of a Supercavitating Vehicle Based on a Radial Basis Function Neural Network Observer Open
Newton’s second law has been applied to create a dynamic model of the lateral motion of a supercavitating vehicle, assuming a stable cavity. However, some states cannot be measured, and there is uncertainty in the lateral model. Aiming to …
View article: A Mapping Method Fusing Forward-Looking Sonar and Side-Scan Sonar
A Mapping Method Fusing Forward-Looking Sonar and Side-Scan Sonar Open
In modern ocean exploration, forward-looking sonar (FLS) provides real-time 2D imaging of the seabed ahead, but its detection range is relatively limited. Conversely, side-scan sonar (SSS) enables large-scale imaging of the seabed during m…
View article: MSFE-UIENet: A Multi-Scale Feature Extraction Network for Marine Underwater Image Enhancement
MSFE-UIENet: A Multi-Scale Feature Extraction Network for Marine Underwater Image Enhancement Open
Underwater optical images have outstanding advantages for short-range underwater target detection tasks. However, owing to the limitations of special underwater imaging environments, underwater images often have several problems, such as n…
View article: Research on the Cultivating Mode of Interdisciplinary Innovative Talents in Bionic Robots
Research on the Cultivating Mode of Interdisciplinary Innovative Talents in Bionic Robots Open
Current scientific problems are becoming increasingly complex and need to be solved through the cross-penetration of disciplines. Cross-disciplinary collaboration has become an important way to solve the major problems facing mankind. Cult…
View article: MLTU: Mixup Long-Tail Unsupervised Zero-Shot Image Classification on Vision-Language Models
MLTU: Mixup Long-Tail Unsupervised Zero-Shot Image Classification on Vision-Language Models Open
Vision-language models, such as Contrastive Language-Image Pretraining (CLIP), have demonstrated powerful capabilities in image classification under zero-shot settings. However, current Zero-Shot Learning (ZSL) relies on manually tagged sa…
View article: Learning mapping by curve iteration estimation For real-time underwater image enhancement
Learning mapping by curve iteration estimation For real-time underwater image enhancement Open
The degradation and attenuation of light in underwater images impose constraints on underwater vision tasks. However, the complexity and the low real-time performance of most current image enhancement algorithms make them challenging in pr…
View article: Sonar Image Target Detection Based on Simulated Stain-like Noise and Shadow Enhancement in Optical Images under Zero-Shot Learning
Sonar Image Target Detection Based on Simulated Stain-like Noise and Shadow Enhancement in Optical Images under Zero-Shot Learning Open
There are many challenges in using side-scan sonar (SSS) images to detect objects. The challenge of object detection and recognition in sonar data is greater than in optical images due to the sparsity of detectable targets. The complexity …
View article: MOCAT: Multi-Omics Integration with Auxiliary Classifiers Enhanced Autoencoder
MOCAT: Multi-Omics Integration with Auxiliary Classifiers Enhanced Autoencoder Open
Background Integrating multi-omics data is emerging as a critical approach in enhancing our understanding of complex diseases. Innovative computational methods capable of managing high-dimensional and heterogeneous datasets are required to…
View article: UIEOGP: an underwater image enhancement method based on optical geometric properties
UIEOGP: an underwater image enhancement method based on optical geometric properties Open
Due to the inconsistent absorption and scattering effects of different wavelengths of light, underwater images often suffer from color casts, blurred details, and low visibility. To address this image degradation problem, we propose a robu…
View article: When SAM Meets Sonar Images
When SAM Meets Sonar Images Open
Segment Anything Model (SAM) has revolutionized the way of segmentation. However, SAM's performance may decline when applied to tasks involving domains that differ from natural images. Nonetheless, by employing fine-tuning techniques, SAM …
View article: LCANet: A Lightweight Context-Aware Network for Bladder Tumor Segmentation in MRI Images
LCANet: A Lightweight Context-Aware Network for Bladder Tumor Segmentation in MRI Images Open
Accurate segmentation of the lesion area from MRI images is essential for diagnosing bladder cancer. However, the precise segmentation of bladder tumors remains a massive challenge due to their similar intensity distributions, various tumo…
View article: Data from Integrative Analysis of Histopathological Images and Genomic Data Predicts Clear Cell Renal Cell Carcinoma Prognosis
Data from Integrative Analysis of Histopathological Images and Genomic Data Predicts Clear Cell Renal Cell Carcinoma Prognosis Open
In cancer, both histopathologic images and genomic signatures are used for diagnosis, prognosis, and subtyping. However, combining histopathologic images with genomic data for predicting prognosis, as well as the relationships between them…
View article: Methods, Table S1-S3, Figure S1-S4 from Integrative Analysis of Histopathological Images and Genomic Data Predicts Clear Cell Renal Cell Carcinoma Prognosis
Methods, Table S1-S3, Figure S1-S4 from Integrative Analysis of Histopathological Images and Genomic Data Predicts Clear Cell Renal Cell Carcinoma Prognosis Open
This file contains: Methods. 1) Aggregation of cell-level features into patient-level features. 2)Training and prediction process of lasso-Cox model. Table S1. The 15 co-expressed gene modules generated by gene co-expression network analys…
View article: Data from Integrative Analysis of Histopathological Images and Genomic Data Predicts Clear Cell Renal Cell Carcinoma Prognosis
Data from Integrative Analysis of Histopathological Images and Genomic Data Predicts Clear Cell Renal Cell Carcinoma Prognosis Open
In cancer, both histopathologic images and genomic signatures are used for diagnosis, prognosis, and subtyping. However, combining histopathologic images with genomic data for predicting prognosis, as well as the relationships between them…
View article: Methods, Table S1-S3, Figure S1-S4 from Integrative Analysis of Histopathological Images and Genomic Data Predicts Clear Cell Renal Cell Carcinoma Prognosis
Methods, Table S1-S3, Figure S1-S4 from Integrative Analysis of Histopathological Images and Genomic Data Predicts Clear Cell Renal Cell Carcinoma Prognosis Open
This file contains: Methods. 1) Aggregation of cell-level features into patient-level features. 2)Training and prediction process of lasso-Cox model. Table S1. The 15 co-expressed gene modules generated by gene co-expression network analys…
View article: Medical matting: Medical image segmentation with uncertainty from the matting perspective
Medical matting: Medical image segmentation with uncertainty from the matting perspective Open
High-quality manual labeling of ambiguous and complex-shaped targets with binary masks can be challenging. The weakness of insufficient expression of binary masks is prominent in segmentation, especially in medical scenarios where blurring…
View article: Identify potential driver genes for PAX-FOXO1 fusion-negative rhabdomyosarcoma through frequent gene co-expression network mining
Identify potential driver genes for PAX-FOXO1 fusion-negative rhabdomyosarcoma through frequent gene co-expression network mining Open
Background Rhabdomyosarcoma (RMS) is a soft tissue sarcoma usually originated from skeletal muscle. Currently, RMS classification based on PAX–FOXO1 fusion is widely adopted. However, compared to relatively clear understanding of the tumor…
View article: A Texture Feature Removal Network for Sonar Image Classification and Detection
A Texture Feature Removal Network for Sonar Image Classification and Detection Open
Deep neural network (DNN) was applied in sonar image target recognition tasks, but it is very difficult to obtain enough sonar images that contain a target; as a result, the direct use of a small amount of data to train a DNN will cause ov…
View article: UIR-Net: A Simple and Effective Baseline for Underwater Image Restoration and Enhancement
UIR-Net: A Simple and Effective Baseline for Underwater Image Restoration and Enhancement Open
Because of the unique physical and chemical properties of water, obtaining high-quality underwater images directly is not an easy thing. Hence, recovery and enhancement are indispensable steps in underwater image processing and have theref…
View article: Sonar Image Target Detection Based on Style Transfer Learning and Random Shape of Noise under Zero Shot Target
Sonar Image Target Detection Based on Style Transfer Learning and Random Shape of Noise under Zero Shot Target Open
With the development of sonar technology, sonar images have been widely used to detect targets. However, there are many challenges for sonar images in terms of object detection. For example, the detectable targets in the sonar data are mor…
View article: A Distinguishable Pseudo-Feature Synthesis Method for Generalized Zero-Shot Learning
A Distinguishable Pseudo-Feature Synthesis Method for Generalized Zero-Shot Learning Open
Generalized zero-shot learning (GZSL) aims to classify seen classes and unseen classes that are disjoint simultaneously. Hybrid approaches based on pseudo-feature synthesis are currently the most popular among GZSL methods. However, they s…
View article: MSEDTNet: Multi-Scale Encoder and Decoder with Transformer for Bladder Tumor Segmentation
MSEDTNet: Multi-Scale Encoder and Decoder with Transformer for Bladder Tumor Segmentation Open
The precise segmentation of bladder tumors from MRI is essential for bladder cancer diagnosis and personalized therapy selection. Limited by the properties of tumor morphology, achieving precise segmentation from MRI images remains challen…