Regularization of deep neural network using a multisample memory model
Deep convolutional neural networks (CNNs) are widely used in computer vision and have achieved significant performance for image classification tasks. Overfitting is a general problem in deep learning models that inhibit the generalization capability of deep models due to the presence of noise, the...
Saved in:
Main Authors: | Tanveer, Muhammad, Siyal, Mohammad Yakoob, Rashid, Sheikh Faisal |
---|---|
Other Authors: | School of Electrical and Electronic Engineering |
Format: | Article |
Language: | English |
Published: |
2025
|
Subjects: | |
Online Access: | https://hdl.handle.net/10356/182482 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | Nanyang Technological University |
Language: | English |
Similar Items
-
REGULARIZATION ON MACHINE LEARNING
by: LIANG SENWEI
Published: (2020) -
Measuring overfitting in nonlinear models: A new method and an application to health expenditures
by: Bilger, M., et al.
Published: (2016) -
Overfitting in semantics-based automated program repair
by: LE, Dinh Xuan Bach, et al.
Published: (2018) -
OVER-FITTING IN PROGRAM REPAIR AND SYNTHESIS
by: GAO XIANG
Published: (2021) -
DeepArc: Modularizing neural networks for the model maintenance
by: REN, Xiaoning, et al.
Published: (2023)