Accurate segmentation of liver vessels is crucial for medical applications due to its pivotal role in diagnosing liver diseases, planning surgical interventions, and assessing treatment effectiveness. In this paper, we present a new dataset for ...

Recovering structures from images with 180∘ or 360∘ FoV is pivotal in computer vision and computational photography, particularly for VR/AR/MR and autonomous robotics applications. Due to varying distortions and the complexity of indoor scenes, ...

Transfer learning (TL) has demonstrated its efficacy in addressing the cross-subject domain adaptation challenges in affective brain-computer interfaces (aBCI). However, previous TL methods usually use a stationary distance, such as Euclidean ...

• MSMMTL uses Mahalanobis distance to assess correlations between subjects and effectively screen suitable source domains.
• MSMMTL utilizes the supervised information from the source domain to learn a more generalized distance ...

Recently, convolutional neural networks (CNNs) and vision transformers (ViTs) have emerged as powerful tools for image restoration (IR). Nonetheless, they encountered some limitations due to their characteristics, such as CNNs sacrificing global ...

Scene structure recovery is a crucial process for assisting scene reconstruction and understanding by extracting vital scene structure information and has been widely used in smart city, VR/AR and intelligent robot navigation. Omnidirectional ...

In recent years, deep learning has gradually become a prevailing way in EEG-based emotion recognition research because it can extract features and classify emotions automatically. To fully exploit the underlying information in EEG signals, we ...

Panorama image has a large 360${}^{\circ }$ field of view, providing rich contextual information for object detection, widely used in virtual reality, augmented reality, scene understanding, etc. However, existing methods for object detection on panorama ...${}^{}$$$

Gliomas are malignant tumors in the central nervous system. Cuproptosis is a newly discovered cell death mechanism targeting lipoylated tricarboxylic acid cycle proteins. Previous studies have found that cuproptosis participates in ...

• The first bioinformatics analysis for the cuproptosis in glioma.
• High-CuAS ...

Recently, Riemannian geometry-based pattern recognition has been widely employed to brain computer interface (BCI) researches, providing new idea for emotion recognition based on electroencephalogram (EEG) signals. Although the ...

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• Emotion recognition combined with Riemannian geometric framework.
• The enhanced ...

In this paper, we propose a continual learning method based on node-importance evaluation and a dynamic architecture model. Our method determines the important nodes according to the value of Laplace operator of each node. Due to the anisotropy of ...

In the past decades, regularized least squares classification (RLSC) is a commonly used supervised classification method in the machine learning filed because it can be easily resolved through the simple matrix analysis and achieve a close-form ...

A major challenge facing camera networks today is how to effectively organizing and visualizing videos in the presence of complicated network connection and overwhelming and even increasing amount of data. Previous works focus on 2D stitching or dynamic ...

Augmented Virtual Environment (AVE) fuses real-time video streaming with virtual scenes to provide a new capability of the real-world run-time perception. Although this technique has been developed for many years, it still suffers from the fusion ...

Motor imagery electroencephalography is widely used in the brain-computer interface systems. Due to inherent characteristics of electroencephalography signals, accurate and real-time multiclass classification is always challenging. In order to solve ...

The annual electric power consumption is one of the most important factors in operation decisions of Chinese electric power generation groups. The grey model is feasible method to deal with this trend extension problem with few data. But the simple ...

With the deterioration of primary energy market supply, it is important to optimize the raw material buying and dispatching. The annual electric power consumption is one of the most important decision making basis to realize this. Because of the ...

This paper aims for developing a method, based on rough set (RS) reduction and wavelet neural network (WNN), to improve the efficiency of short-term load forecasting (STLF). The RS reduction could erase redundant characters and this makes it possible to ...

Writing force is an important biometric attribute for on-line writer verification But it is often neglected or introduced deficiently for the limitation of the existing input device In this paper, a text-independent on-line writer verification algorithm ...

At present, many researches have been done on the handwriting using static or dynamic signals, but no tools could acquire all handwriting information including kinematics and kinetics of pen-point, including strokes of pen-up and pen-down, velocity and ...