A survey on machine and deep learning in semiconductor industry: methods, opportunities, and challenges
AC Huang, SH Meng, TJ Huang - Cluster Computing, 2023 - Springer
The technology of big data analysis and artificial intelligence deep learning has been
actively cross-combined with various fields to increase the effect of its original low single …
actively cross-combined with various fields to increase the effect of its original low single …
Feature reused network: a fast segmentation network model for strip steel surfaces defects based on feature reused
Q Feng, F Li, H Li, X Liu, J Fei, S Xu, C Lu, Q Yang - The Visual Computer, 2024 - Springer
The strip steel is a common metallic material with a wide range of applications in various
industries. However, the issue of surface defects that possess high concealment and low …
industries. However, the issue of surface defects that possess high concealment and low …
Improving surface defect detection with context-guided asymmetric modulation networks and confidence-boosting loss
Segmentation networks based on deep learning are widely used in the field of surface
defect detection to ensure product quality. However, due to the complexity of defects and …
defect detection to ensure product quality. However, due to the complexity of defects and …
Accurate detection of surface defects by decomposing unreliable tasks under boundary guidance
D Kang, J Lai, Y Han - Expert Systems with Applications, 2024 - Elsevier
Intelligent defect detection systems based on deep learning have great potential for
industrial applications to ensure product quality. However, the success of such data-driven …
industrial applications to ensure product quality. However, the success of such data-driven …
Prototype-guided domain adaptive one-stage object detector for defect detection
Abstract Domain adaptive defect detection aims to identify defects in an unlabeled target
dataset by leveraging an annotated source dataset that shares similarities. This task poses a …
dataset by leveraging an annotated source dataset that shares similarities. This task poses a …
Teacher-Student Collaboration: Effective Semi-Supervised Model for Defect Instance Segmentation
Recent defect instance segmentation methods heavily rely on pixel-level annotated images.
However, acquiring labeled defect data from modern manufacturing industries takes …
However, acquiring labeled defect data from modern manufacturing industries takes …
X-ray PCB defect automatic diagnosis algorithm based on deep learning and artificial intelligence
Y Liu, P Wang, J Liu, C Liu - Neural Computing and Applications, 2023 - Springer
As a main electronic material, X-ray circuits are widely used in various electronic devices,
and their quality has an important impact on the overall quality of electronic products. In the …
and their quality has an important impact on the overall quality of electronic products. In the …
Music emotion recognition using deep convolutional neural networks
T Li - Journal of Computational Methods in Science and …, 2024 - journals.sagepub.com
Traditional music emotion recognition (MER) faces problems such as lack of contextual
information, inaccurate recognition of music emotions, and difficulty in handling nonlinear …
information, inaccurate recognition of music emotions, and difficulty in handling nonlinear …
Real-Time Defect Detection Network Based on Hybrid Attention Mechanism for Small-Size Printed Circuit Boards
C Wang, X Wei, X Wu, X Jiang - 2023 IEEE International …, 2023 - ieeexplore.ieee.org
The defect detection of Printed Circuit boards (PCB) is challenging due to the complex
image background, various types of defects, and small size of defects. This paper develops …
image background, various types of defects, and small size of defects. This paper develops …