Overfitting Detection
Overfitting Detection is a methodological contribution in pattern evaluation that identifies when a model's performance on training data significantly exceeds its performance on unseen data due to excessive complexity or overadaptation to training noise.
236
Publications
29.5K
Citations
767
Authors
346
Institutions
Publications per year
2017–2026
153
Parents
236
Cascade R-CNN: Delving Into High Quality Object Detection
Zhaowei Cai, Nuno Vasconcelos · 2018 · 6.8K citations
An Overview of Overfitting and its Solutions
Ying Xue · Journal of Physics Conference Series · 2019 · 2.2K citations · Full text
1–5 of 236
767
3
h-index
3
h-index
3
h-index
3
h-index
2
h-index
1–5 of 767
346
University of Pennsylvania
Philadelphia, United States
5 h-index
8 publications
439 citations
Tongji University
Shanghai, China
4 h-index
8 publications
144 citations
University of California, Berkeley
Berkeley, United States
4 h-index
11 publications
799 citations
Carnegie Mellon University
Pittsburgh, United States
4 h-index
8 publications
339 citations

Chinese Academy of Sciences
Beijing, China
4 h-index
8 publications
243 citations
University of Oxford
Oxford, United Kingdom
3 h-index
3 publications
144 citations

Xidian University
Xi'an, China
3 h-index
6 publications
385 citations

National Taiwan University
Taipei, Taiwan
3 h-index
10 publications
245 citations
1–8 of 346
Repository · 22 publications · 1.5K citations
16
h-index
5 publications · 546 citations
5
h-index
4 publications · 543 citations
4
h-index
4 publications · 126 citations
4
h-index
3 publications · 2.3K citations
3
h-index
1–5