To achieve precision and lightweight design for pavement distress detection in complex scenarios, an improved YOLOv8n model, named YOLOv8n-Ultra, is constructed. The Coordinate Attention (CA) module is embedded into the C2f layer of the backbone netw...
Underwater object detection is essential for the advancement of automated aquaculture operations. Addressing the challenges of low detection accuracy and insufficient generalization capabilities for underwater targets, this paper focuses on the devel...
Barnyard grass is a major noxious weed in paddy fields. Accurate and efficient identification of barnyard grass is crucial for precision field management. However, existing deep learning models generally suffer from high parameter counts and computat...
This paper proposes DCGAN-YOLOv8n, an integrated framework that significantly advances small-sample target detection by synergizing generative adversarial feature enhancement with multi-scale representation learning. The model’s core contributi...
Zucchini growth in greenhouse environments presents significant challenges for fruit recognition and picking point localization due to characteristics such as foliage occlusion, high density, structural complexity, and diverse fruit morphologies. Cur...
Electric wheelchairs are the primary means of transportation that enable individuals with disabilities to move independently to their desired locations. This paper introduces a novel, low-cost smart wheelchair system designed to enhance the mobility...
To address the challenges of rapid and accurate grape variety identification in natural orchard environments, along with the demand for efficient deployment on mobile devices, we propose in this paper YOLOv11n-GrapeLite, a lightweight model built upo...
This study addresses the challenges of tomato maturity recognition in natural environments, such as occlusion caused by branches and leaves, and the difficulty in detecting stacked fruits. To overcome these issues, we propose a novel YOLOv8n-CA metho...
Tea bud localization detection not only ensures tea quality, improves picking efficiency, and advances intelligent harvesting, but also fosters tea industry upgrades and enhances economic benefits. To solve the problem of the high computational compl...
Frequent occurrences of pests and diseases in tomatoes severely restrict yield and quality improvements. Traditional detection methods are labor-intensive and prone to errors, while advancements in deep learning provide a promising solution for rapid...
Ensuring fire safety is essential to protect life and property, but modern infrastructure and complex settings require advanced fire detection methods. Traditional object detection systems, often reliant on manual feature extraction, may fall short,...
This study addresses the problem of detecting occluded apples in complex unstructured environments in orchards and proposes an apple detection and segmentation model based on improved YOLOv8n-SGW-YOLOv8n. The model improves apple detection and segmen...
China’s Yunnan Province, known for its tea plantations, faces significant challenges in smart pest management due to its ecologically intricate environment. To enable the intelligent monitoring of pests within tea plantations, this study introd...
Sheep facial expressions are valuable indicators of their pain levels, playing a critical role in monitoring their health and welfare. In response to challenges such as missed detections, false positives, and low recognition accuracy in sheep facial...
Traffic sign detection is an important functional component of autonomous driving systems and plays a crucial role in road environment perception, assisted driving decision-making, and traffic safety assurance. However, under complex scenarios such a...
The accurate detection of litchi fruit cluster is the key technology of litchi picking robot. In the natural environment during the day, due to the unstable light intensity, uncertain light angle, background clutter and other factors, the identificat...
The pitaya is a common fruit in southern China, but the growing environment of pitayas is complex, with a high density of foliage. This intricate natural environment is a significant contributing factor to misidentification and omission in the detect...
In the study of aircraft wake target detection, as the wake evolves and develops, the detection area of the LiDAR often shows the presence of two distinct vortices, one on each side. Sometimes, only a single wake vortex may be present. This can lead...
Every day, millions of meteoroids enter the atmosphere and ablate, forming a long plasma trail. It is a strongly scattering object for electromagnetic waves and can be effectively detected by meteor radar at altitudes between 70 km and 140 km. Its ec...
In the field of smart grid monitoring, real-time defect detection for overhead transmission lines is crucial for ensuring the safety and stability of power systems. This paper proposes a defect detection model for overhead transmission lines based on...
To address the challenges of tomato maturity detection in natural environments—such as interference from complex backgrounds and the difficulty in distinguishing adjacent fruits with similar maturity levels—this study proposes a lightweig...
Currently, object detection-based rail fastener defect detection methods still face challenges such as limited detection categories, insufficient accuracy, and high computational complexity. To this end, the YOLOv8n-FDD, an advanced multi-category fa...
In order to detect rice false smut quickly and accurately, a lightweight false smut detection model, YOLOv8n-MBS, was proposed in this study. The model introduces the C2f_MSEC module to replace C2f in the backbone network for better extraction of key...
Accurate fruit target identification is crucial for autonomous harvesting robots in complex orchards, where image segmentation using deep learning networks plays a key role. To address the trade-off between segmentation accuracy and inference efficie...
The timely and accurate detection of whether or not workers in an industrial environment are correctly wearing personal protective equipment (PPE) is paramount for worker safety. However, current PPE detection faces multiple inherent challenges, incl...
In order to improve the efficiency of fine segmentation and obstacle removal in the road of tea plantation in hilly areas, a lightweight and high-precision DR-YOLO instance segmentation algorithm is proposed to realize environment awareness. Firstly,...
Traffic-sign detection and recognition (TSDR) is crucial to avoiding harm to pedestrians, especially children, from intelligent connected vehicles and has become a research hotspot. However, due to motion blurring, partial occlusion, and smaller sign...
Accurate detection and counting of oat ears are essential for yield estimation but remain challenging in complex field environments due to occlusion, significant scale variation, and fluctuating lighting. The aim of this study is to develop a high-pr...
Accurate detection and segmentation of young ‘Yuluxiang’ pear fruits at the fruit thinning stage are crucial for the development of intelligent fruit thinning robots. To address the challenges in recognition and segmentation of young &lsq...
Brevipalpus spp. are widespread pests on wine grapes in northwest China and have generated a major threat to the local wine grape industry in recent years. We advanced the YOLOv8n model (object detection algorithm), termed SEM-YOLOv8n, to predict the...
Wind turbine blade defect detection in complex environments is challenged by weak defect features, missed crack detections, and false detections caused by background interference. To address these problems, this study proposes an improved YOLOv8n-bas...
Synthetic aperture radar is widely applied to ship detection due to generating high-resolution images under diverse weather conditions and its penetration capabilities, making SAR images a valuable data source. However, detecting multi-scale ship tar...
The visual signal object detection technology of deep learning, as a high-precision perception technology, can be adopted in various image analysis applications, and it has important application prospects in the utilization and protection of marine b...
To address the challenges of significant size variations, inconspicuous textures, weak edges, and background interference in wire harness insulation surface defect detection, this paper proposes WHD-YOLOv8n, an improved YOLOv8n-based defect detection...
Grading tea leaves efficiently in a natural environment is a crucial technological foundation for the automation of tea-picking robots. In this study, to solve the problems of dense distribution, limited feature-extraction ability, and false detectio...
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...
Pleurotus ostreatus, classified under the phylum Basidiomycota, order Agaricales, and family Pleurotaceae, is a prevalent gray edible fungus. Its physical damage not only compromises quality and appearance but also significantly diminishes market val...
Pitaya fruit is a significant agricultural commodity in southern China. The traditional method of determining the ripeness of pitaya by humans is inefficient, it is therefore of the utmost importance to utilize precision agriculture and smart farming...
Global warming has driven a marked increase in forest fire occurrences, underscoring the critical need for timely and accurate detection to mitigate fire-related losses. Existing forest fire detection algorithms face limitations in capturing flame an...
To address the low recognition accuracy of models for coal gangue images in intelligent coal preparation systems—especially in identifying small target coal gangue due to factors such as camera angle changes, low illumination, and motion blur&m...
Natural latex harvest is pushing the boundaries of unmanned agricultural production in rubber milk collection via integrated robots in hilly and mountainous regions, such as the fixed and mobile tapping robots widely deployed in forests. As there are...
To tackle core challenges in detecting ship targets within synthetic aperture radar (SAR) images—including coherent speckle noise interference, complex background clutter, and multi-scale target distribution—this paper proposes a high-acc...
Accurate picking-point localization and pose estimation are essential for selective robotic harvesting of marigolds, yet side-view imaging suffers from slender pedicel morphology, frequent occlusions, and weak visual contrast at the corolla–ped...
Seed quality testing is crucial for ensuring food security and stability. To accurately detect the germination status of corn seeds during the paper medium germination test, this study proposes a corn seed germination status detection model based on...
Camera-based visual sensing provides a non-destructive and scalable approach for monitoring strawberry diseases and pests in greenhouse environments. However, greenhouse images acquired under practical cultivation conditions often contain early-stage...
Object detection has a vital impact on the analysis and interpretation of visual scenes. It is widely utilized in various fields, including healthcare, autonomous driving, and vehicle surveillance. However, complex scenes containing small, occluded,...
Grapes are an important cash crop that contributes to the rapid development of the agricultural economy. The harvesting of ripe fruits is one of the crucial steps in the grape production process. However, at present, the picking methods are mainly ma...
To address the demands of intelligent safflower harvesting scenarios, which require a safflower recognition model with both low computational cost and high detection performance, this paper proposes a lightweight improved model based on YOLOv11n, ter...
To address challenges like manual processes, complicated detection methods, high false alarm rates, and frequent errors in identifying defects on steel surfaces, this research presents an innovative detection system, YOLOv10n-SFDC. The study focuses...
Ecological flow management is important for maintaining ecosystem stability and promoting sustainable development. Dynamic ecological flow regulation depends on precise real-time monitoring of water levels and flow velocities. To address challenges i...
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