Abstract
We present a comprehensive, stacking-based framework for combining deep learning with good old-fashioned machine learning, called Deep GOld. Our framework involves ensemble selection from 51 retrained pretrained deep networks as first-level models, and 10 machine-learning algorithms as second-level models. Enabled by today’s state-of-the-art software tools and hardware platforms, Deep GOld delivers consistent improvement when tested on four image-classification datasets: Fashion MNIST, CIFAR10, CIFAR100, and Tiny ImageNet. Of 120 experiments, in all but 10 Deep GOld improved the original networks’ performance.
Original language | English |
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Article number | 85 |
Journal | SN Computer Science |
Volume | 4 |
Issue number | 1 |
DOIs | |
State | Published - 1 Jan 2023 |
Keywords
- Deep learning
- Image analysis
- Machine learning
- Pattern recognition
ASJC Scopus subject areas
- General Computer Science
- Computer Science Applications
- Computer Networks and Communications
- Computer Graphics and Computer-Aided Design
- Computational Theory and Mathematics
- Artificial Intelligence