Due to the limited memory and computing resources in the real application of target detection, the method is challenging to implement on mobile and embedded devices. In order to achieve the balance between detection accuracy and speed in pedestrian-i...
The random dumping of garbage in rivers has led to the continuous deterioration of water quality and affected people’s living environment. The accuracy of detection of garbage floating in rivers is greatly affected by factors such as floating s...
The recognition of lane line type plays an important role in the perception of advanced driver assistance systems (ADAS). In actual vehicle driving on roads, there are a variety of lane line type and complex road conditions which present significant...
Frequent landslide disasters on the Loess Plateau in northwestern China have had a serious impact on the lives and production of the people in the region due to the fragile ecological environment and severe soil erosion. The effective monitoring and...
Aerial remote sensing image object detection, based on deep learning, is of great significance in geological resource exploration, urban traffic management, and military strategic information. To improve intractable problems in aerial remote sensing...
Intense, large-scale forest fires are damaging and very challenging to control. Locations, where various types of fire behavior occur, vary depending on environmental factors. According to the burning site of forest fires and the degree of damage, th...
The accurate detection of coal gangue is an important prerequisite for the intelligent sorting of coal gangue. Aiming at existing coal gangue detection methods, which have problems such as low detection accuracy and complex model structure, a multi-s...
The aging population has drastically increased in the past two decades, stimulating the development of devices for healthcare and medical purposes. As one of the leading potential risks, the injuries caused by accidental falls at home are hazardous t...
Synthetic aperture radar (SAR) is an active ground-surveillance radar system, which can observe targets regardless of time and weather. Passenger aircrafts are important targets for SAR, as it is of great importance for accurately recognizing the typ...
As a vital part of autonomous driving, vehicle detection, especially for outdoor small target vehicles, has attracted great attention from researchers during recent years. To ameliorate the difficulty in accurately identifying outdoor small vehicle t...
The high salinity, humidity, and oxygen-rich environments of coastal marine areas pose serious corrosion risks to metal structures, particularly in equipment such as ships, offshore platforms, and port facilities. With the development of artificial i...
At present, deep learning has been widely used in SAR ship target detection, but the accurate and real-time detection of multi-scale targets still faces tough challenges. CNN-based SAR ship detectors are challenged to meet real-time requirements beca...
Aerial insulator defect images have some features. For instance, the complex background and small target of defects would make it difficult to detect insulator defects quickly and accurately. To solve the problem of low accuracy of insulator defect d...
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...
To meet the demands of the food industry for automatic sorting of block-shaped foods using DELTA robots, a machine vision detection method capable of quickly identifying such foods needs to be studied. This paper proposes a lightweight model that inc...
The identification and detection of microalgae are essential for the development and utilization of microalgae resources. Traditional methods for microalgae identification and detection have many limitations. Herein, a Feature-Enhanced YOLOv7 (FE-YOL...
Currently, aeroplane images captured by camera sensors are characterized by their small size and intricate backgrounds, posing a challenge for existing deep learning algorithms in effectively detecting small targets. This paper incorporates the RFBNe...
The efficient identification of rice pests and diseases is crucial for preventing crop damage. To address the limitations of traditional manual detection methods and machine learning-based approaches, a new rice pest and disease recognition model bas...
The extraction and analysis of plant phenotypic characteristics are critical issues for many precision agriculture applications. An improved YOLOv5 model was proposed in this study for accurate node detection and internode length estimation of crops...
To further improve the detection of smoke and small target smoke in complex backgrounds, a novel smoke detection model called RepVGG-YOLOv7 is proposed in this paper. Firstly, the ECA attention mechanism and SIoU loss function are applied to the YOLO...
Fastener screws are critical components of rail fasteners. For the fastener screw maintenance robot, an image-based fast fastener screw detection method is urgently needed. In this paper, we propose a light-weight model named FSS-YOLO based on YOLOv5...
To address the issues of low detection accuracy, slow detection speed, high missed detection rate, and high false detection rate in the detection of surface defects on pre-impregnated composite materials during the automated tape laying and winding p...
Aiming at the problem of insufficient feature extraction, low precision, and recall in sea surface ship detection, a YOLOv5 algorithm based on lightweight convolution and attention mechanism is proposed. We combine the receptive field enhancement mod...
X-ray contraband detection plays an important role in the field of public safety. To solve the multi-scale and obscuration problem in X-ray contraband detection, we propose a material-aware path aggregation network to detect and classify contraband i...
Printed circuit boards (PCBs) are extensively used to assemble electronic equipment. Currently, PCBs are an integral part of almost all electronic products. However, various surface defects can still occur during mass production. An enhanced YOLOv5s...
A method for classifying floating garbage in rivers using a modified YOLOv11 algorithm is proposed to solve the problem of poor recognition of river floating objects using the conventional object detection algorithms. This approach first integrates a...
Dwarf apple is one of the most important forms of garden economy, which has become a new engine for rural revitalization. The effective detection of coloring and ripening apples in complex environments is important for the sustainable development of...
Ship instance segmentation in remote sensing images is essential for maritime applications such as intelligent surveillance and port management. However, this task remains challenging due to dense target distributions, large variations in ship scales...
With the exponential growth of road transportation infrastructure, the need for pavement maintenance has increased significantly. Surface cracking represents a critical evaluation metric in roadway inspection. Conventional manual inspection methods i...
Ship fires are one of the main factors that endanger the safety of ships; because the ship is far away from land, the fire can be difficult to extinguish and could often cause huge losses. The engine room has many pieces of equipment and is the princ...
Safety helmet wearing plays a major role in protecting the safety of workers in industry and construction, so a real-time helmet wearing detection technology is very necessary. This paper proposes an improved YOLOv4 algorithm to achieve real-time and...
Surface-defect detection is crucial for assuring the quality of strip-steel manufacturing. Strip-steel surface-defect detection requires defect classification and precision localization, which is a challenge in real-world applications. In this resear...
Apple leaf diseases can significantly affect the yield and quality of apple crops. However, conventional manual detection methods are inefficient and highly susceptible to subjective judgment, rendering them inadequate for large-scale agricultural pr...
Landslide detection is crucial for natural disaster risk management. Deep-learning-based object-detection algorithms have been shown to be effective in landslide studies. However, advanced algorithms currently used for landslide detection require hig...
The complex environment along railway lines, characterized by low imaging quality, strong background interference, and densely distributed small objects, causes existing detection models to suffer from low accuracy in practical applications. To tackl...
Rose tea is a type of flower tea in China’s reprocessed tea category, which is divided into seven grades, including super flower, primary flower, flower bud, flower heart, yellow flower, scattered flower, and waste flower. Grading rose tea into...
Conventional inspections in car damage assessments depend on visual judgments by human inspectors, which are labor-intensive and prone to fraudulent practices through manipulating damages. Recent advancements in artificial intelligence have given ris...
Defect detection in rail fasteners constitutes a fundamental requirement for ensuring safe and reliable railway operations. Confronted with increasingly demanding inspection requirements of modern rail networks, traditional manual visual inspection m...
Existing detection methods face a huge challenge in identifying insulators with minor defects when targeting transmission line images with complex backgrounds. To ensure the safe operation of transmission lines, an improved YOLOv7 model is proposed t...
The objects in UAV aerial images have multiple scales, dense distribution, and occlusion, posing considerable challenges for object detection. In order to address this problem, this paper proposes a real-time multi-scale object detection method based...
Aiming at the problem of detection difficulties caused by the characteristics of high similarity and disorderly arrangement of workpieces in dense scenes of industrial production lines, this paper proposes a workpiece detection method based on improv...
Train wheels are crucial components for ensuring the safety of trains. The accurate and fast identification of wheel tread defects is necessary for the timely maintenance of wheels, which is essential for achieving the premise of conditional repair....
To address the issues of decreased detection accuracy, false detections, and missed detections caused by scale differences between near and distant targets and environmental factors (such as lighting and water waves) in surface target detection tasks...
Hazardous material vehicles are a non-negligible mobile source of danger in transport and pose a significant safety risk. At present, the current detection technology is well developed, but it also faces a series of challenges such as a significant a...
Object detection in unmanned aerial vehicle (UAV) images has become a popular research topic in recent years. However, UAV images are captured from high altitudes with a large proportion of small objects and dense object regions, posing a significant...
A method for counting the number of citrus fruits based on the improved YOLOv5s algorithm combined with the DeepSort tracking algorithm is proposed to address the problem of the low accuracy of counting citrus fruits due to shading and lighting facto...
Background: To address issues in current deep learning models for detecting defects on industrial bearing surfaces, such as large parameter sizes and low precision in identifying small defects, we propose a lightweight detection algorithm for small-s...
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...
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...
Dragon fruit stem disease significantly affects both the quality and yield of dragon fruit. Therefore, there is an urgent need for an efficient, high-precision intelligent detection method to address the challenge of disease detection. To address the...
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