Testing convolutional neural network based deep learning systems: a statistical metamorphic approach
Machine learning technology spans many areas and today plays a significant role in addressing a wide range of problems in critical domains, i.e., healthcare, autonomous driving, finance, manufacturing, cybersecurity, etc. Metamorphic testing (MT) is considered a simple but very powerful approach in...
Saved in:
Main Authors: | Faqeer ur Rehman, Clemente Izurieta |
---|---|
Format: | Article |
Language: | English |
Published: |
PeerJ Inc.
2025-01-01
|
Series: | PeerJ Computer Science |
Subjects: | |
Online Access: | https://peerj.com/articles/cs-2658.pdf |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Metamorphic testing of named entity recognition systems: A case study
by: Yezi Xu, et al.
Published: (2022-08-01) -
Vulnerability detection method for blockchain smart contracts based on metamorphic testing
by: Jinfu CHEN, et al.
Published: (2023-10-01) -
Comparative study on coal rank gradient under different types of metamorphism
by: Jielin LU, et al.
Published: (2024-12-01) -
Analysis and Optimization on Workspace of 2-PrRS-PR(P)S Parallel Metamorphic Mechanism
by: Ma Kun, et al.
Published: (2020-03-01) -
Safety-Critical Oracles for Metamorphic Testing of Deep Learning LiDAR Point Cloud Object Detectors
by: Simon Speth, et al.
Published: (2025-01-01)