Pedestrian detection technology refers to identifying pedestrians within the field of view and is widely used in smart cities, public safety surveillance, and other scenarios. However, in real-world complex scenes, challenges such as high pedestrian...
This study aims to address a series of challenges in infrared small target detection, particularly in complex backgrounds and high-noise environments. In response to these issues, we propose a deep learning model called the Feature Multi-Scale Enhanc...
Object detection in unmanned aerial vehicle (UAV) scenes is a challenging task due to the varying scales and complexities of targets. To address this, we propose a novel object detection model, AFE-YOLOv8, which integrates three innovative modules: t...
To improve the accuracy of material identification under low contrast conditions, this paper proposes an improved YOLOv4-tiny target detection method based on an adaptive self-order piecewise enhancement and multiscale feature optimization. The model...
For large oil-immersed transformers, their metal-enclosed structure poses significant challenges for direct visual inspection of internal defects. To ensure the effective detection of internal insulation defects, this study employs a self-developed m...
With the rapid development and widespread application of drones across various fields, drone recognition and classification at medium and long distances have become increasingly important yet challenging tasks. This paper proposes a novel network arc...
The point clouds scanned by lidar are generally sparse, which can result in fewer sampling points of objects. To perform precise and effective 3D object detection, it is necessary to improve the feature representation ability to extract more feature...
Action recognition is essential in security monitoring, home care, and behavior analysis. Traditional solutions usually leverage particular devices, such as smart watches, infrared/visible cameras, etc. These methods may narrow the application areas...
Welding is a critical joining process in modern manufacturing, with defects contributing to 50–80% of structural failures. Traditional inspection methods are often inefficient, subjective, and inconsistent. To address challenges in weld defect...
Unlike the high imaging radiation dose of computed tomography (CT), cone-beam CT (CBCT) has smaller radiation dose and presents less harm to patients. Therefore, CBCT is often used for target delineation, dose planning, and postoperative evaluation i...
The complex and harsh working environment of rolling bearings cause the fault characteristics in vibration signal contaminated by the noise, which make fault diagnosis difficult. In this paper, a feature enhancement method of rolling bearing signal b...
Arbitrary-oriented object detection (AOOD) is a crucial task in aerial image analysis but is also faced with significant challenges. In current AOOD detectors, commonly used multi-scale feature fusion modules fall short in spatial and semantic inform...
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...
Recently, ship detection in synthetic aperture radar (SAR) images has received extensive attention. Most of the current ship detectors preset dense anchor boxes to achieve spatial alignment with ground-truth (GT) objects. Then, the detector defines t...
To address the issues of loss of important detailed features, insufficient contrast enhancement, and high computational complexity in existing low-light image enhancing methodologies, this paper presents a low-light image enhancement network (MSF-ACA...
Data-driven methods are widely applied to predict the remaining useful life (RUL) of lithium-ion batteries, but they generally suffer from two limitations: (i) the potentials of features are not fully exploited, and (ii) the parameters of the predict...
Underwater image enhancement (UIE) is a key technology in the fields of underwater robot navigation, marine resources development, and ecological environment monitoring. Due to the absorption and scattering of different wavelengths of light in water,...
In complex marine environments, underwater images often suffer from color distortion, blur, and poor visibility. Existing underwater image enhancement methods predominantly rely on the U-net structure, which assigns the same weight to different resol...
In this study, we propose an advanced category of a fuzzy adaptive neural network (FANN) based on a feature self-enhancement unit (FSU) and statistical selection methods (SSMs). Undoubtedly, the raw data contain a large amount of information with var...
The quality of silkworm cocoons affects the quality and cost of silk processing. It is necessary to sort silkworm cocoons prior to silk production. Cocoon images consist of fine-grained images with large intra-class differences and small inter-class...
Aiming at the problem of appearance drift and susceptibility to noise interference in visual place recognition (VPR), we propose DD–DPFE: a Dynamic Difference and Dual-Path Feature Enhancement method. Embedding differential attention mechanisms...
There are problems associated with facial expression recognition (FER), such as facial occlusion and head pose variations. These two problems lead to incomplete facial information in images, making feature extraction extremely difficult. Most current...
With the rapid development of intelligent transportation systems, traffic sign detection plays a crucial role in ensuring driving safety and preventing accidents. However, detecting small traffic signs in complex road environments remains a significa...
Convolutional neural networks (CNNs) play an important role in hyperspectral image (HSI) classification due to their powerful feature extraction ability. Multiscale information is an important means of enhancing the feature representation ability. Ho...
Visually impaired individuals frequently encounter difficulties in detecting and avoiding obstacles in the wild. To address this issue, we propose an obstacle detection method for visual navigation assistance, named YOLO-OD. To improve the ability to...
Accurate identification of the combustion state in municipal solid waste incineration (MSWI) processes is crucial for achieving efficient, low-emission, and safe operation. However, existing methods often struggle with stable and reliable recognition...
Image matching is a key research issue in the intelligent processing of remote sensing images. Due to the large phase differences or apparent differences in ground features between unmanned aerial vehicle imagery and satellite imagery, as well as the...
Global navigation satellite system (GNSS) positions include various useful signals and some unmodeled errors. In order to enhance the accuracy and extract the features of the GNSS daily time sequence, an improved method of complete ensemble empirical...
UAV infrared sensor technology plays an irreplaceable role in various fields. High-altitude infrared images present significant challenges for feature extraction due to their uniform texture and color, fragile and variable edge information, numerous...
Underwater images often suffer from degradation due to scattering and absorption. With the development of artificial intelligence, fully supervised learning-based models have been widely adopted to solve this problem. However, the enhancement perform...
Concrete surface crack detection plays a crucial role in infrastructure maintenance and safety. Deep learning-based methods have shown great potential in this task. However, under real-world conditions such as poor image quality, environmental interf...
Inspection of the integrality of components and connecting parts is an important task to maintain safe and stable operation of transmission lines. In view of the fact that the scale difference of the auxiliary component in a connecting part is large...
Hyperspectral sparse unmixing (SU) networks have recently received considerable attention due to their model hyperspectral images (HSIs) with a priori spectral libraries and to capture nonlinear features through deep networks. This method effectively...
In low-light conditions, UAV localization faces substantial challenges due to reduced visibility, elevated noise levels, and diminished contrast. To address these issues, we propose a low-light-optimized visual localization framework that integrates...
Electric power operation violation recognition (EPOVR) is essential for personnel safety, achieved by detecting key objects in electric power operation scenarios. Recent methods usually use the YOLOv8 model to achieve EPOVR; however, the YOLOv8 model...
In recent years, frequent forest fires have seriously threatened the earth’s ecosystem and people’s lives and safety. With the development of machine vision and unmanned aerial vehicle (UAVs) technology, UAV monitoring combined with machi...
In this paper, we focus on the multi-target tracking (MOT) task in satellite videos. To achieve efficient and accurate tracking, we propose a transformer-distillation-based end-to-end joint detection and tracking (JDT) method. Specifically, (1) consi...
Recently, research on hyperspectral image classification (HSIC) methods has made significant progress. However, current models commonly only focus on the primary features, overlooking the valuable information contained in secondary features that can...
In the field of visual tracking, discriminative correlation filter (DCF)-based trackers have made remarkable achievements with their high computational efficiency. The crucial challenge that still remains is how to construct qualified samples without...
Road defect detection is essential for timely road damage repair and traffic safety assurance. However, existing object detection algorithms suffer from insufficient accuracy in detecting small road surface defects and are prone to missed detections...
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...
Low-speed hoist bearings are characterized by fault features that are weak and difficult to extract. Multipoint optimal minimum entropy deconvolution adjusted (MOMEDA) is an effective method for extracting periodic pulses in a signal. However, the de...
Medical image segmentation plays a crucial role in medical image processing, focusing on the automated extraction of regions of interest (such as organs, lesions, etc.) from medical images. This process supports various clinical applications, includi...
Existing salient object detection methods for optical remote sensing images still face certain limitations due to complex background variations, significant scale discrepancies among targets, severe background interference, and diverse topological st...
The ‘black box’ nature of machine learning (ML) approaches makes it challenging to understand how most artificial intelligence (AI) models make decisions. Explainable AI (XAI) aims to provide analytical techniques to understand the behavi...
For unmanned aerial vehicle (UAV) ground crew marshalling tasks, the accuracy of skeleton-based action recognition is often limited by the high similarity of motion patterns across action categories as well as variations in individual performance. To...
Recent advancements in speech enhancement (SE) have leveraged deep neural networks with multi-domain features to improve noise suppression. This study introduces a wavelet-enhanced adaptive FullSubNet (WA-FSN) framework that replaces traditional shor...
Face recognition systems typically face actual challenges like facial pose, illumination, occlusion, and ageing that significantly impact the recognition accuracy. In this paper, a robust face recognition system that uses Multi-task Cascaded Convolut...
The extraction of the micro-Doppler (m-D) feature based on time-frequency distribution (TFD) is of great significance for target detection and identification. To improve the feature extraction performance, numerous TFDs have been developed, with the...
Landslide detection in mountainous regions remains highly challenging due to complex terrain conditions, heterogeneous surface textures, and the fragmented distribution of landslide features. To address these limitations, this study proposes an enhan...
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