image captioning is a challenging task that lies at the intersection of Computer vision and Natural Language processing. There exists a legion of works that generate meaningful and realistic descriptions of images. Re...
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A laser line detection algorithm for the positioning of construction robots based on Line Segment Detector (LSD) and an improved least squares method (LSM) is proposed to address the line finding and localization requ...
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ISBN:
(纸本)9798350325621
A laser line detection algorithm for the positioning of construction robots based on Line Segment Detector (LSD) and an improved least squares method (LSM) is proposed to address the line finding and localization requirements in actual construction operations. After preprocessing and edge detection of the input image, the LSD algorithm is utilized to detect line segments representing the laser lines for positioning. These line segments are then converted into a point set containing information about the laser lines' positions. To overcome the limitations of traditional least squares method that relies on vertical errors, an improved least squares method is employed to fit the centerline of the laser lines, which serves as a reference for subsequent robot localization. Experimental results demonstrate that the proposed algorithm accurately detects and fits the centerline of the laser lines in the input image, and exhibits high robustness and accuracy.
This paper introduces the structure and operation mode of automatic production line based on the actual situation of laser quenching automatic production line of tool in enterprises. Robot vision integrates workpiece ...
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ISBN:
(纸本)9781665464680
This paper introduces the structure and operation mode of automatic production line based on the actual situation of laser quenching automatic production line of tool in enterprises. Robot vision integrates workpiece positioning coordinates with robot coordinates to realize the positioning and grasping function of robot through machinevision. Focus on OpenCV imageprocessing methods. This paper describes its principle and possible problems from the aspects of system structure, robot coordinate calibration, visual identification and positioning and software design.
With the rapid development of autonomous driving technology, safety perception has become a critical component in ensuring the reliability and safety of these systems. However, challenges persist, such as traffic acci...
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The fusion of imageprocessing and machine learning has opened new avenues in dermatological disease detection, facilitating accurate diagnosis and treatment. Leveraging a diverse dataset comprising images of various ...
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Quantum machine Learning (QML) promises the transformative potential in computer vision by utilizing quantum computing to facilitate faster high-dimensional data processing. In this paper, we will go through some of t...
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In the process of daily operation and maintenance, the detection of abnormal video quality still mainly depends on manual subjective decision-making, which is difficult to meet the growing requirements of video servic...
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The defects of the Printed Circuit Board(PCB) directly affect the performance and reliability of electronic products. Therefore, detecting PCB defects is crucial. Lightweight models in PCB production inspection can ef...
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ISBN:
(纸本)9798350349405;9798350349399
The defects of the Printed Circuit Board(PCB) directly affect the performance and reliability of electronic products. Therefore, detecting PCB defects is crucial. Lightweight models in PCB production inspection can effectively reduce equipment costs, but they exhibit limited feature extraction capabilities. Moreover, complex background conditions can interfere with the model's ability to locate and recognize small defects. To address these challenges, we propose LSDM-PCB, a lightweight PCB defect detection model based on YOLOv8n. Firstly, we improve the network structure to reduce the number of model parameters while enhancing the model's ability to capture small defects. Additionally, we adopt Receptive-Field Attention Convolution(RFAConv) as a downsampling module to enhance the model's feature extraction by considering the importance of each feature within the receptive field. Finally, we propose a Global and Local Mixed Attention(GLMA) mechanism to strengthen multi-scale feature representation, allowing the model to focus more on small defects. Results show LSDM-PCB reduces model parameters by 74% and improves mAP50 to 96.8%, a 2.7% enhancement compared to the baseline model YOLOv8n.
Tibetan medicine, one of the four major traditional medical systems in the world, employs urine diagnosis as a unique and widely used method for disease identification in Tibetan medicine. This study developed a joint...
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Recently, efficient image coding for machines method is widely required under machinevision task-oriented coding scenarios. To achieve higher task accuracy under a certain bitrate constraint, existing solutions take ...
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