Pcbnet: A lightweight convolutional neural network for defect inspection in surface mount technology

H Wu, R Lei, Y Peng - IEEE Transactions on Instrumentation …, 2022 - ieeexplore.ieee.org
Prereflow automatic optical inspection (AOI) has been widely used to ensure product quality
in surface mount technology (SMT). When confronted with a complex industrial environment …

A survey on hardware vulnerability analysis using machine learning

Z Pan, P Mishra - IEEE Access, 2022 - ieeexplore.ieee.org
Electronic systems rely on efficient hardware, popularly known as system-on-chip (SoC), to
support its core functionalities. A typical SoC consists of diverse components gathered from …

PCBSegClassNet—A light-weight network for segmentation and classification of PCB component

D Makwana, S Mittal - Expert Systems with Applications, 2023 - Elsevier
PCB component classification and segmentation can be helpful for PCB waste recycling.
However, the variance in shapes and sizes of PCB components presents crucial challenges …

Defect detection of printed circuit board based on lightweight deep convolution network

J Shen, N Liu, H Sun - IET Image Processing, 2020 - Wiley Online Library
With the rapid development of the electronic industry, the defect detection of printed circuit
board (PCB) components is becoming more and more important. The types of PCB …

Application of convolutional neural network in defect detection of 3C products

W Ming, C Cao, G Zhang, H Zhang, F Zhang… - IEEE …, 2021 - ieeexplore.ieee.org
Based on the rapid development of semiconductors, integrated circuits and the Internet. 3C
products such as computers, tablets, mobile phones and smart TVs have become an …

[HTML][HTML] Implementation and potentials of a machine vision system in a series production using deep learning and low-cost hardware

H Würschinger, M Mühlbauer, M Winter, M Engelbrecht… - Procedia CIRP, 2020 - Elsevier
For manufacturing processes there is a need to ensure an efficient production and to fulfill
the increasing quality requirements. To handle these challenges, Machine Vision Systems …

Chip-last (RDL-first) fan-out panel-level packaging (FOPLP) for heterogeneous integration

JH Lau, CT Ko, CY Peng, KM Yang… - Journal of …, 2020 - meridian.allenpress.com
In this investigation, the chip-last, redistribution-layer (RDL)–first, fan-out panel-level
packaging (FOPLP) for heterogeneous integration is studied. Emphasis is placed on the …

Computer-vision-based integrated circuit recognition using deep learning

YN Voon, KM Ang, YH Chong, WH Lim… - Proceedings of the 6th …, 2022 - Springer
Computer vision technology is widely implemented in electronic manufacturing industry to
detect the defects on printed circuit board (PCB). However, the wrong attachment of …

A Comprehensive Taxonomy of Visual Printed Circuit Board Defects

DS Koblah, OP Dizon-Paradis, J Schubeck… - Journal of Hardware and …, 2023 - Springer
The globalization of printed circuit board (PCB) production has expanded the avenues to
introduce vulnerabilities into the electronics supply chain. Malicious parties may modify or …

Enhancing EfficientNet-YOLOv4 for Integrated Circuit Detection on Printed Circuit Board (PCB)(December 2023)

TS Chi, MN Ab Wahab, ASA Mohamed… - IEEE …, 2024 - ieeexplore.ieee.org
Ensuring the quality and functionality of printed circuit boards (PCBs) during manufacturing
requires precise, automated visual inspection. Detecting integrated circuits (ICs) on PCBs …