Name
Title | ||
|---|---|---|
Unsupervised novelty pattern classification of shmoo plots for visualizing the test results of integrated circuits |
Abstract | ||
|---|---|---|
•Shmoo plots in semiconductor manufacturing are used for indicating device state.•We address high-dimensional and multiclass imbalance challenges for shmoo plots.•We introduce a feature extraction process for presenting clear shmoo plot patterns.•We propose a two-stage clustering process to solve multiclass imbalance situations.•To demonstrate the applicability of the proposed model, real field data is used. |
Year | DOI | Venue |
|---|---|---|
2022 | 10.1016/j.eswa.2022.117341 | Expert Systems with Applications |
Keywords | DocType | Volume |
Shmoo plot,Class imbalance,High dimensionality,Unlabeled data,Feature extraction,Clustering | Journal | 202 |
ISSN | Citations | PageRank |
0957-4174 | 0 | 0.34 |
References | Authors | |
0 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Hyun Soo Shin | 1 | 0 | 0.34 |
| Youngju Kim | 2 | 0 | 0.34 |
| Chang Ouk Kim | 3 | 0 | 0.34 |
| Sung Ho Park | 4 | 1 | 1.70 |