The work considers formal structure and features of the readability indices widely employed in various information and education fields, including theory of communication, cognitive psychology, linguistics, and multiple applications. In spite of the...
For both traditional classification and current popular deep learning methods, the limited sample classification problem is very challenging, and the lack of samples is an important factor affecting the classification performance. Our work includes t...
Urban mobility structure detection and functional distribution learning are significant for urban planning and management. However, existing methods have limitations in handling complex urban data and capturing global spatial structure features. To d...
To tackle problems such as the destruction of topological structures and the loss of detailed features in the simplification of 3D building models, we propose a 3D building model simplification algorithm that considers detailed features and topologic...
Hamstring injury has been considered one of the most common exercise-induced injuries in sports. Hamstring injuries mostly occur proximal to the biceps femoris. However, the reasons and mechanisms remain unclear. To summarize hamstring morphological...
Peripheral nerve blocking (PNB) is a standard procedure to support regional anesthesia. Still, correct localization of the nerve’s structure is needed to avoid adverse effects; thereby, ultrasound images are used as an aid approach. In addition, imag...
Tree species classification is a ubiquitous task in the forest inventory field. Only directly measured feature vectors have been applied to most existing methods that use LiDAR technology for tree species classification. As a result, it is difficult...
Pollination by sexual deception specifically attracts male insects, through the floral scent and particular morphological features of the flower that serve as visual and tactile stimuli. The unique bond between the Ophrys speculum orchid and the male...
Feature selection for multiple types of data has been widely applied in mild cognitive impairment (MCI) and Alzheimer’s disease (AD) classification research. Combining multi-modal data for classification can better realize the complementarity o...
The current study on community evolution prediction ignores the problem of internal community topology characteristics and does not take feature sets extraction into account. Therefore, the MF-PSF (Multivariate Feature sets and Potential Structural F...
City-scale forecasting is essential for both electric-vehicle (EV) charging operations (e.g., peak management and resource allocation) and urban mobility management (e.g., road-network flow monitoring and incident response). Spatio-temporal graph neu...
Unmanned aerial vehicles (UAVs) and light detection and ranging (LiDAR) can be used to analyze the geomorphic features in complex plateau mountains. Accordingly, a UAV–LiDAR system was adopted in this study to acquire images and lidar point-clo...
Feature tracking in image collections significantly affects the efficiency and accuracy of Structure from Motion (SFM). Insufficient correspondences may result in disconnected structures and incomplete components, while the redundant correspondences...
Plant growth is closely related to the structure of its stem. The ultrasonic echo signal of the plant stem carries much information on the stem structure, providing an effective means for analyzing stem structure characteristics. In this paper, we pr...
The hyperspectral feature extraction technique is one of the most popular topics in the remote sensing community. However, most hyperspectral feature extraction methods are based on region-based local information descriptors while neglecting the corr...
Leaf area index (LAI), as one of the important crop field phenotypes, plays a crucial role in evaluating crop growth and yield. The remote sensing method for crop parameters monitoring makes it possible to obtain crop LAI in a large area, efficiently...
By using signal processing and statistical analysis methods simultaneously, many heterogeneous features can be produced to describe the bearings fault with more comprehensive and discriminant information. At same time, there may exist redundant or ir...
With the rapid development of airborne Light Detection and Ranging (LiDAR) sensors, point clouds have been widely applied in fields such as surveying and mapping engineering, intelligent monitoring, and autonomous driving. However, the irregular stru...
In this paper, we present a novel unsupervised feature selection method termed robust matrix factorization with robust adaptive structure learning (RMFRASL), which can select discriminative features from a large amount of multimedia data to improve t...
Accurate fish detection in complex underwater environments remains challenging due to scattering, low contrast, blur, occlusion, and background interference, which significantly degrade appearance-based representations. To address these issues, this...
The classification of marine vessels is one of the important problems of maritime traffic. To fully exploit the complementarity between different features and to more effectively identify marine vessels, a novel feature structure fusion method based...
How to obtain internal cavity features and perform image matching is a great challenge for laparoscopic 3D reconstruction. This paper proposes a method for detecting and associating vascular features based on dual-branch weighted fusion vascular stru...
The prior knowledge of protein structural class may offer useful clues on understanding its functionality as well as its tertiary structure. Though various significant efforts have been made to find a fast and effective computational approach to addr...
Structural damage detection is of significance for maintaining the structural health. Currently, data-driven deep learning approaches have emerged as a highly promising research field. However, little progress has been made in studying the relationsh...
Co-Ni ferrite is one of the crucial materials for the electronic industry. A partial substitution with a rare-earth metal brings about modification in crystal lattice and broadens knowledge in the discovery of new magnetic material. Current work repo...
Feature matching plays a crucial role in the process of 3D reconstruction based on the structure from motion (SfM) technique. For a large collection of oblique images, feature matching is one of the most time-consuming steps, and the matching result...
Unsupervised feature selection is difficult when relevance must be inferred without labels, and redundancy, outliers, and sample-localized geometry can distort marginal criteria. This study presents Geometry-Supported Residual Feature Selection (GSR-...
Online rumors spread rapidly through social media, which is a great threat to public safety. Existing solutions are mainly based on content features or propagation structures for rumor detection. However, due to the variety of strategies in creating...
Synthetic aperture radar (SAR) target recognition tasks face the dilemma of limited training samples. The fusion of target scattering features improves the ability of the network to perceive discriminative information and reduces the dependence on tr...
One of the most significant problems affecting a concrete bridge’s safety is cracks. However, detecting concrete bridge cracks is still challenging due to their slender nature, low contrast, and background interference. The existing convolution...
The task of visual geo-localization based on street-view images estimates the geographical location of a query image by recognizing the nearest reference image in a geo-tagged database. This task holds considerable practical significance in domains s...
Thin-walled conformal cooling structures are essential for the thermal management of complex curved electronic and aerospace devices. The traditional topology optimization of conformal cooling structures requires cumbersome post-processing reconstruc...
Facial recognition is one of the most challenging and interesting problems within the field of computer vision and pattern recognition. During the last few years, it has gained special attention due to its importance in relation to current issues suc...
In this paper, we propose an imaging method for seafloor features based on multipath arrival structures. The bistatic sonar system employed consists of a vertical transmitting array and a horizontal towed array. The conventional back projection (BP)...
Small ships in remote sensing images have blurred details and are difficult to detect. Existing algorithms usually detect small ships based on predefined anchors with different sizes. However, limited by the number of different sizes, it is difficult...
Currently, screen content images (SCIs) are widely used in our modern society. However, since SCIs have distinctly different properties compared to natural images, traditional quality assessment methods of natural images cannot precisely evaluate the...
Structural health monitoring (SHM) is critical for ensuring the safety and longevity of structures, yet existing methodologies often face challenges such as high data dimensionality, lack of interpretability, and reliance on extensive label datasets....
Chemical modifications are the standard for small interfering RNAs (siRNAs) in therapeutic applications, but predicting their off-target effects remains a significant challenge. Current approaches often rely on sequence-based encodings, which fail to...
To address the limitations in capturing complex semantic features between entities and the incomplete acquisition of entity and relationship information by existing patent knowledge graph reasoning algorithms, we propose a reasoning method that integ...
Deep convolutional neural networks have demonstrated significant performance improvements in face super-resolution tasks. However, many deep learning-based approaches tend to overlook the inherent structural information and feature correlation across...
Power line detection plays an important role in an automated UAV-based electricity inspection system, which is crucial for real-time motion planning and navigation along power lines. Previous methods which adopt traditional filters and gradients may...
Quantifying the health of civil infrastructure using sensor data remains challenging, as degradation-related signals are typically weak and obscured by dominant environmental and operational effects. In structural health monitoring (SHM), this often...
A flame’s structural feature is a crucial parameter required to comprehensively understand the interaction between turbulence and flames. The generation and evolution processes of the structure feature have rarely been investigated in lean blow...
In the task of integrated circuit micrograph acquisition, image super-resolution reconstruction technology can significantly enhance acquisition efficiency. With the advancement of deep learning techniques, the performance of image super-resolution r...
Optical and synthetic aperture radar (SAR) image matching is fundamental to numerous remote sensing applications. Although phase congruency-based methods have been widely adopted for this task, the structural features they extract remain inherently s...
Accurate detection and identification of obstacles plays an important role in the navigation and behavior planning of the patrol robot. Aiming at the patrol robot with camera mounted symmetrically, an obstacle detection method based on structural con...
The LiDAR point cloud has been widely used in scenarios of automatic driving, object recognition, structure reconstruction, etc., while it remains a challenging problem in line structure extraction, due to the noise and accuracy, especially in data a...
Balancing detection performance and computational efficiency is critical for sustainable pavement disease detection in energy-constrained scenarios. However, existing visual methods often struggle to adapt to structural transformations and capture cr...
Infrared and visible image match is an important research topic in the field of multi-modality image processing. Due to the difference of image contents like pixel intensities and gradients caused by disparate spectrums, it is a great challenge for i...
Change detection on bitemporal synthetic aperture radar (SAR) images is a key branch of SAR image interpretation. However, it is challenging due to speckle and unavoidable registration errors within bitemporal SAR images. A key issue is whether and h...
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