Comparison of Deep Transfer Learning Against Contrastive Learning in Industrial Quality Applications for Heavily Unbalanced Data Scenarios When Data Augmentation Is Limited
AI-oriented quality inspection in manufacturing often faces highly imbalanced data, as defective products are rare, and there are limited possibilities for data augmentation. This paper presents a systematic comparison between Deep Transfer Learning (DTL) and Contrastive Learning (CL) under such cha...
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| Main Authors: | Amir Farmanesh, Raúl G. Sanchis, Joaquín Ordieres-Meré |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2025-05-01
|
| Series: | Sensors |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1424-8220/25/10/3048 |
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