Related references
Note: Only part of the references are listed.
Article
Green & Sustainable Science & Technology
Junlong Tang et al.
Summary: In this paper, an improved detection algorithm of PCB surface defects based on YOLOv5, named PCB-YOLO, is proposed to address the problems of low network accuracy, slow speed, and a large number of model parameters in PCB defect detection. The algorithm obtains more suitable anchors for the dataset using the K-means++ algorithm and adds a small target detection layer to focus on more small target information. Swin transformer is embedded into the backbone network, and a united attention mechanism is constructed to improve the network's analysis ability. Model volume compression is achieved by introducing depth-wise separable convolution. The EIoU loss function is used to optimize the regression process and enhance the localization ability of small targets. Experimental results show that PCB-YOLO achieves a satisfactory balance between performance and consumption, with 95.97% mAP at 92.5 FPS, making it more accurate and faster than many other algorithms for real-time and high-precision detection of product surface defects.
Article
Automation & Control Systems
Wujin Jiang et al.
Summary: In order to improve the detection efficiency of PCB defects, a joint multiscale PCB defect target detection and attention mechanism, named RAR-SSD, was proposed. By using the lightweight receptive field block module (RFB-s) with an attention mechanism module, the proposed network built a wider range of effective focused features and efficiently fused low-level feature information with high-level feature information. The optimized algorithm improved the fault recognition accuracy of PCBs by 2.23% over the original SSD algorithm, with a recall rate of 6.51% and an F1 value of 4.85%, showing significant improvements in detection performance and outperforming YOLOv3 and YOLOv5 algorithms.
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
(2023)
Article
Computer Science, Information Systems
Bowei Du et al.
Summary: An enhanced YOLO-MBBi network is proposed to detect surface defects on printed circuit boards (PCBs) and address the shortcomings of existing methods. Experimental results show that YOLO-MBBi outperforms YOLOv5s in terms of accuracy and real-time performance, achieving higher mAP50 and recall values while requiring fewer FLOPs and achieving a higher FPS value. The metrics also showed satisfactory accuracy when tested with another dataset, meeting the needs of industrial production.
Article
Engineering, Manufacturing
Cui-jin Li et al.
Summary: This article presents a PCB defect detection algorithm based on the extended feature pyramid network model. By incorporating multiscale fusion and introducing focal loss function, the algorithm addresses the challenge of small object detection. Experimental results show that the algorithm achieves a mean average precision (mAP) of 96.2% on the public PCB dataset, surpassing the state-of-the-art methods.
IEEE TRANSACTIONS ON COMPONENTS PACKAGING AND MANUFACTURING TECHNOLOGY
(2022)
Article
Computer Science, Artificial Intelligence
Xin Liu et al.
Summary: Improving detection accuracy is essential for industrial processes like producing printed circuit boards (PCBs). This paper introduces a method using a new loss function called Gaussian intersection of union (GsIoU) to enhance accuracy, achieving significant improvements over existing methods on the PCBC dataset.
EXPERT SYSTEMS WITH APPLICATIONS
(2022)
Article
Automation & Control Systems
Guangyan Bao et al.
Summary: This paper surveys the cooperative control of heterogeneous multi-agent systems (HMASs) subject to specific constraints. HMASs are classified into weak and strong categories based on different cooperative behaviors, and control strategies are discussed for dealing with various constraints on agent dynamics and communication networks. The latest results on cooperative control under different constraints are summarized, and conclusions are drawn along with possible future research directions.
SYSTEMS SCIENCE & CONTROL ENGINEERING
(2022)
Article
Automation & Control Systems
Han Li et al.
Summary: This paper reviews the use of mathematical tools to enhance LFIA performance, and proposes a novel taxonomy. It also presents the outlook of developing POCT in conjunction with other state-of-the-art techniques, and highlights the importance of applying computational intelligence methods in boosting POCT development.
INTERNATIONAL JOURNAL OF SYSTEMS SCIENCE
(2022)
Article
Computer Science, Information Systems
Wei Chen et al.
Summary: In this paper, a Transformer-YOLO network detection model is proposed to address the low accuracy and efficiency in PCB defect detection. The model utilizes an improved clustering algorithm to generate suitable anchor boxes, adopts Swin Transformer for feature extraction, and incorporates convolutional and attention mechanism modules for enhanced detection performance.
Article
Computer Science, Information Systems
Ligang Wu et al.
Summary: This paper proposes a deep learning detection method, GSC YOLOv5, for defect and fault detection of printed circuit boards. The method integrates a lightweight network and a dual attention mechanism to optimize the detection precision and real-time performance.
Article
Engineering, Electrical & Electronic
Zhigang Ling et al.
Summary: This article proposes a novel deep Siamese semantic segmentation network for PCB welding defect detection, which combines the similarity measurement of the Siamese network with the encoder-decoder semantic segmentation network. The network effectively addresses the challenges faced by deep learning in PCB defect detection, achieving semantic segmentation of small defects.
IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT
(2022)
Article
Automation & Control Systems
Jingyang Mao et al.
Summary: Recursive filtering for nonlinear systems is a core technology in modern industrial systems, facing challenges such as communication scheduling, limited bandwidth, and security vulnerability. It is of utmost significance in theory and great importance in applications to establish engineering-feasible recursive filtering algorithms for networked nonlinear systems. This paper provides an up-to-date survey of existing nonlinear filtering techniques and raises several challenging issues for further research and practical applications.
INTERNATIONAL JOURNAL OF SYSTEMS SCIENCE
(2021)
Article
Engineering, Electrical & Electronic
Zhengding Luo et al.
Summary: A novel end-to-end deep feature fusion network with multiple attention mechanisms is proposed for joint iris-periocular recognition, achieving more accurate and adaptive recognition. The network outperforms traditional biometric recognition and other iris-periocular recognition methods on two publicly available datasets.
IEEE SIGNAL PROCESSING LETTERS
(2021)
Article
Automation & Control Systems
Jie Xu et al.
Summary: This paper focuses on the fault estimation problem for a class of nonlinear systems with sensor gain degradation and stochastic protocol based on strong tracking filtering. The method constructs an augmented system and introduces a fading factor into the filter structure to address sensor gain degradation and data conflicts in multi-signal transmission. Simulation results demonstrate the effectiveness and applicability of the proposed approach.
SYSTEMS SCIENCE & CONTROL ENGINEERING
(2021)
Article
Computer Science, Artificial Intelligence
Haiyong Chen et al.
JOURNAL OF INTELLIGENT MANUFACTURING
(2020)
Article
Engineering, Electrical & Electronic
Mohammad Jubran et al.
IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY
(2020)
Article
Computer Science, Artificial Intelligence
Jie Hu et al.
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE
(2020)
Article
Computer Science, Information Systems
Bing Hu et al.
Article
Engineering, Multidisciplinary
S. Neethu et al.
IEEE TRANSACTIONS ON INDUSTRY APPLICATIONS
(2019)
Article
Computer Science, Artificial Intelligence
Runwei Ding et al.
CAAI TRANSACTIONS ON INTELLIGENCE TECHNOLOGY
(2019)
Article
Computer Science, Artificial Intelligence
Vilas H. Gaidhane et al.
PATTERN ANALYSIS AND APPLICATIONS
(2018)
Article
Computer Science, Artificial Intelligence
Heeyoul Choi et al.
Article
Computer Science, Artificial Intelligence
Shaoqing Ren et al.
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE
(2017)
Article
Computer Science, Artificial Intelligence
Kaiming He et al.
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE
(2015)
