Aiming at the problem of manual feature extraction and insufficient mining of feature information for partial discharge pattern recognition under different insulation faults in GIS, a deep learning model based on phase and timing features with Swin T...
Although the accurate lithological segmentation of outcrops plays a key role in hydrocarbon exploration, complex field environments and substantial scale variations within outcrops, particularly in extremely thin sand–mudstone interbeds, presen...
Surface cracks are alluded to as one of the early signs of potential damage to infrastructures. In the same vein, their detection is an imperative task to preserve the structural health and safety of bridges. Human-based visual inspection is acknowle...
Detecting small-scale objects remains a critical challenge with limited pixel information, complex backgrounds, and varying imaging conditions. To tackle these challenges, we propose an innovative high-precision detection framework (DRF-YOLO) that in...
With the continuous growth of electricity demand, the safety and stability of transmission lines have become increasingly important. To ensure the reliability of power supply, it is essential to promptly detect and address foreign object intrusions o...
Pigs play vital roles in the food supply, economic development, agricultural recycling, bioenergy, and social culture. Pork serves as a primary meat source and holds extensive applications in various dietary cultures, making pigs indispensable to hum...
Target detection in UAV aerial photography scenarios faces challenges of small targets and complex backgrounds. Thus, we proposed an improved YOLOv11n small-target detection algorithm. First, a detection head is added to the 160 × 160 resolutio...
Forest fires pose a significant threat to forest resources and wildlife. To balance accuracy and parameter efficiency in forest fire detection, this study proposes an improved model, Mcan-YOLO, based on YOLOv7. In the Neck section, the asymptotic fea...
The widespread application of drone technology has raised security concerns, as unauthorized drones can lead to illegal intrusions and privacy breaches. Traditional detection methods often fall short in balancing performance and lightweight design, m...
Small objects in UAV imagery are easily obscured by sensor noise, adverse illumination, and weather-like appearance degradation. To address this problem, this paper proposes YOLO-ROSS, a lightweight detector built on YOLOv11. Its two architectural co...
With the development of smart aquaculture, the demand for accuracy for underwater target detection has increased. However, traditional target detection methods have proven to be inefficient and imprecise due to the complexity of underwater environmen...
Deep learning has injected a new sense of vitality into the field of image inpainting, allowing for the creation of more realistic inpainted images that are difficult to distinguish from the original ones. However, this also means that the malicious...
Edge detection is one of the fundamental computer vision tasks. Recent methods for edge detection based on a convolutional neural network (CNN) typically employ the weighted cross-entropy loss. Their predicted results being thick and needing post-pro...
Wearing gloves during machinery operation in workshops is essential for preventing accidental injuries, such as mechanical damage and burns. Ensuring that workers are wearing gloves is a key strategy for accident prevention. Consequently, this study...
The automatic detection of traffic accidents plays an increasingly vital role in advancing intelligent traffic monitoring systems and improving road safety. Leveraging computer vision techniques offers a promising solution, enabling rapid, reliable,...
Wampee (Clausena lansium) harvesting currently relies heavily on manual labor, but automation is significantly hindered by clustered fruit growth patterns, small fruit sizes, and complex orchard backgrounds, which make accurate detection highly chall...
General target detection with deep learning has made tremendous strides in the past few years. However, small target detection sometimes is associated with insufficient sample size and difficulty in extracting complete feature information. For safety...
Object detection in complex environments, such as challenging lighting conditions, adverse weather, and target occlusions, poses significant difficulties for existing algorithms. To address these challenges, this study introduces a collaborative solu...
Addressing the low accuracy and slow detection speed experienced by algorithms based on deep learning for a leather defect detection task, a lightweight and improved leather defect detection algorithm, dubbed YOLOv8-AGE, has been proposed based on YO...
The safety of belt conveyor operation is of great importance during coal conveyance. This paper proposes a multi-task-based GSSA-YOLOM algorithm for monitoring the state of belt conveyors, which utilizes segmentation head to detect foreign objects an...
Building instances extraction is an essential task for surveying and mapping. Challenges still exist in extracting building instances from high-resolution remote sensing imagery mainly because of complex structures, variety of scales, and interconnec...
This study proposes an intelligent agricultural pest monitoring system that integrates mechanical control with deep learning to address issues in traditional systems, such as pest accumulation interference, image contrast degradation under complex li...
Object detection in complex scenarios such as construction sites, electric power operations, and resource exploration often suffers from low accuracy and frequent missed or false detections. To address these challenges, this study proposes a modified...
Unmanned aerial vehicles (UAVs), renowned for their rapid deployment, extensive data collection, and high spatial resolution, are crucial in locating distressed individuals during search and rescue (SAR) operations. Challenges in maritime search and...
Robotic peach harvesting represents a pivotal strategy for reducing labor costs and improving production efficiency. The fundamental prerequisite for a harvesting robot to successfully complete picking tasks is the accurate recognition of fruit growt...
This study focused on addressing the issue of delayed root system development in mulberry trees during aerosol cultivation, which is attributed to the asynchronous growth of branches and buds. To tackle this challenge, we propose an intelligent folia...
To solve key challenges in machine vision-driven online defect recognition of soft packaging, such as inadequate ability to capture defect deformation, difficulty in extracting defect features, and limited generalization performance of models, an onl...
Addressing the challenges related to urban water bodies is essential for advancing urban planning and development. Therefore, obtaining precise and timely information regarding urban water bodies is of paramount importance. To address issues such as...
Due to the challenges of pest detection in complex environments, this research introduces a lightweight network for tobacco pest identification leveraging enhancements in YOLOv8 technology. Using YOLOv8 large (YOLOv8l) as the base, the neck layer of...
It is important to achieve the 3D reconstruction of UAV remote sensing images in deep learning-based multi-view stereo (MVS) vision. The lack of obvious texture features and detailed edges in UAV remote sensing images leads to inaccurate feature poin...
Accurate detection and timely management of high-voltage transmission accessories are crucial for ensuring the safe operation of power transmission. Existing network models suffer from issues like low precision in accessory detection, elevated model...
Accurate, rapid, and intelligent stored-grain insect detection and counting are important for integrated pest management (IPM). Existing stored-grain insect pest detection models are often not suitable for detecting tiny insects on the surface of gra...
Due to the unique distance and angles involved in satellite remote sensing, ships appear with a small pixel area in images, leading to insufficient feature representation. This results in suboptimal performance in ship detection, including potential...
In the process of fabric production, various types of defects affect the quality of a fabric. However, due to the wide variety of fabric defects, the complexity of fabric textures, and the concealment of small target defects, current fabric defect de...
Due to the black and glossy appearance of the carbon fiber prepreg bundle surface, the accurate identification of surface defects in automated fiber placement (AFP) presents a high level of difficulty. Currently, the enhanced YOLOv7 algorithm demonst...
Aircraft cargo compartment fires constitute a significant type of aviation fire, posing a grave threat to aviation safety. To guard against and respond to such fires, existing aircraft cargo compartments are equipped with smoke detection fire detecto...
Citrus diseases can lead to surface defects on citrus fruits, adversely affecting their quality. This study aims to accurately identify citrus defects against varying backgrounds by focusing on four types of diseases: citrus black spot, citrus canker...
In response to the need for precision and intelligence in the assessment of transplanting machine operation quality, this study addresses challenges such as low accuracy and efficiency associated with manual observation and random field sampling for...
Human Pose Estimation (HPE) remains challenging due to scale variation, occlusion, and high computational costs. Standard methods often struggle to capture detailed spatial information when keypoints are obscured, and they typically rely on computati...
Cotton is a crucial crop in the global textile industry, with major production regions including China, India, and the United States. While smart agricultural mechanization technologies, such as automated irrigation and precision pesticide systems, h...
Underwater fish detection and multi-object tracking support marine ecological monitoring, underwater robot inspection, and fish behavior analysis. In a tracking-by-detection framework, this study targets three specific problems: unstable detection in...
To tackle the frequent missed and false detection issues arising from the tiny scale of objects and strong background clutter in UAV aerial photography scenarios, this paper proposes a novel algorithm named SODet-YOLO for UAV aerial imagery. First, t...
In order to improve the target visual recognition and localization accuracy of robotic arms in complex scenes with similar targets, hybrid recognition and localization methods based on an industrial camera and depth camera are proposed. First, accord...
In the realm of autonomous driving, practical driving scenarios are fraught with numerous complexities, including inclement weather conditions, nighttime blurriness, and ambient light sources that significantly hinder drivers’ ability to discer...