Forest ecosystems, as vital natural resources, are increasingly endangered by wildfires. Effective forest fire management relies on the accurate and early detection of small–scale flames and smoke. However, the complex and dynamic forest enviro...
Violence is a serious threat to societal health; preventing violence in airports, airplanes, and spacecraft is crucial. This study proposes the Violence-YOLO model to detect violence accurately in real time in complex environments, enhancing public s...
In contemporary society, fatigue driving is a major cause of traffic accidents, making accurate and timely detection critical for improving driving safety. In this study, we propose a novel fatigue detection model, CSA-YOLO, designed to enhance the a...
As healthcare costs rise due to aging populations and chronic illnesses, optimized care solutions are urgently needed. Gesture recognition and fall detection are critical for intelligent companion robots in healthcare. However, current deep learning...
Automated ripeness detection in large-scale strawberry cultivation is often challenged by complex backgrounds, significant target scale variation, and small object size. To address these problems, an efficient strawberry ripeness detection model, YOL...
Face detection serves as the prerequisite and foundation for individual sheep and goat identification. Considering the practical detection process, the facial region of sheep and goats shares similarities with the torso texture features, which could...
Human Pose Estimation (HPE) plays a critical role in medical applications, particularly within nursing robotics for patient monitoring. Despite its importance, HPE faces several challenges, including high rates of false positives and negatives, strin...
Timely detection of bridge surface defects is important for structural safety assessment and inspection efficiency. To address defect scale variation, complex background interference, and the high computational cost of RT-DETR-R50, this study propose...
The offshore environment is complex during automatic target annotation at sea, and the difference between the focal lengths of visible and infrared sensors is large, thereby causing difficulties in matching multitarget electro-optical images at sea....
For modern agricultural management, the accuracy of plant identification is crucial. However, the task becomes challenging because crops and weeds at early growth stages often exhibit similar color, leaf morphology, and texture in two-dimensional ima...
Steel, a fundamental material in modern industry, is widely used across manufacturing, construction, and energy sectors. Steel surface defects exhibit characteristics such as multiple classes, multi-scale features, small detection targets, and low-co...
Defect detection constitutes one of the most crucial processes in industrial production. With a continuous increase in the number of defect categories and samples, the defect detection model underpinned by deep learning finds it challenging to expand...
Pest control in economic forests is a crucial aspect of sustainable forest resource management, yet it faces bottlenecks such as low efficiency and high miss rates for small objects. Based on the RT-DETR model, this paper proposes LightFAD-DETR, a li...
The ripeness of tomatoes is a critical factor influencing both their quality and yield. Currently, the accurate and efficient detection of tomato ripeness in greenhouse environments, along with the implementation of selective harvesting, has become a...
To address the challenges posed by complex background interference, varying target sizes, and high species diversity in bird detection tasks in the Dongting Lake region, this paper proposes an enhanced bird detection model named Birds-YOLO, based on...
With the advancement of computer vision technology, the demand for fruit recognition in agricultural automation is increasing. To improve the accuracy and efficiency of recognizing young red pears, this study proposes an improved model based on the l...
Accurately detecting and counting abnormal fish behaviors in aquaculture is essential. Timely detection allows farmers to take swift action to protect fish health and prevent economic losses. This paper proposes an enhanced high-precision detection a...
Micro-defects, such as ink spots, scratches, and sintering formed during the screen printing process of photovoltaic cells, significantly impair module performance. Traditional machine vision methods exhibit limited detection efficiency and high fals...
The progress of object detection technology is crucial for obtaining extensive scene information from aerial perspectives based on computer vision. However, aerial image detection presents many challenges, such as large image background sizes, small...