A review and analysis of automatic optical inspection and quality monitoring methods in electronics industry
Electronics industry is one of the fastest evolving, innovative, and most competitive
industries. In order to meet the high consumption demands on electronics components …
industries. In order to meet the high consumption demands on electronics components …
Significant applications of machine learning for COVID-19 pandemic
Machine learning is an innovative approach that has extensive applications in prediction.
This technique needs to be applied for the COVID-19 pandemic to identify patients at high …
This technique needs to be applied for the COVID-19 pandemic to identify patients at high …
Symbiotic relationship between machine learning and Industry 4.0: A review
Industry 4.0 though launched less than a decade ago, has revolutionized the way
technologies are being used. It has found its application in almost every field of …
technologies are being used. It has found its application in almost every field of …
End-to-end deep learning framework for printed circuit board manufacturing defect classification
We report a complete deep-learning framework using a single-step object detection model
in order to quickly and accurately detect and classify the types of manufacturing defects …
in order to quickly and accurately detect and classify the types of manufacturing defects …
One-shot recognition of manufacturing defects in steel surfaces
Quality control is an essential process in manufacturing to make the product defect-free as
well as to meet customer needs. The automation of this process is important to maintain high …
well as to meet customer needs. The automation of this process is important to maintain high …
Global contextual attention augmented YOLO with ConvMixer prediction heads for PCB surface defect detection
K **a, Z Lv, K Liu, Z Lu, C Zhou, H Zhu, X Chen - Scientific reports, 2023 - nature.com
To solve the problem of missed and false detection caused by the large number of tiny
targets and complex background textures in a printed circuit board (PCB), we propose a …
targets and complex background textures in a printed circuit board (PCB), we propose a …
An efficient SMD-PCBA detection based on YOLOv7 network model
Z Li, J Yan, J Zhou, X Fan, J Tang - Engineering Applications of Artificial …, 2023 - Elsevier
Abstract Modern Printed Circuit Board Assembly (PCBA) manufacturing processes require
more accurate and robust defect inspection methods. Despite the potential of deep learning …
more accurate and robust defect inspection methods. Despite the potential of deep learning …
Pcb defect detection using denoising convolutional autoencoders
Printed Circuit boards (PCBs) are one of the most important stages in making electronic
products. A small defect in PCBs can cause significant flaws in the final product. Hence …
products. A small defect in PCBs can cause significant flaws in the final product. Hence …
Artificial Intelligence powered Internet of Things and smart public service
Y Ma, K **, C Wu, L Chen, H Shi, D Chong - Library Hi Tech, 2020 - emerald.com
Purpose The Internet of Things (IoT) has attracted a lot of attention in both industrial and
academic fields for recent years. Artificial intelligence (AI) has developed rapidly in recent …
academic fields for recent years. Artificial intelligence (AI) has developed rapidly in recent …
A hybrid model for financial time‐series forecasting based on mixed methodologies
Z Luo, W Guo, Q Liu, Z Zhang - Expert Systems, 2021 - Wiley Online Library
This paper proposes a hybrid model that combines ensemble empirical mode
decomposition (EEMD), autoregressive integrated moving average (ARIMA), and Taylor …
decomposition (EEMD), autoregressive integrated moving average (ARIMA), and Taylor …