Test Automation with Grad-CAM Heatmaps - A Future Pipe Segment in MLOps for Vision AI?

@article{Borg2021TestAW,
  title={Test Automation with Grad-CAM Heatmaps - A Future Pipe Segment in MLOps for Vision AI?},
  author={Markus Borg and Ronald Jabangwe and Simon {\AA}berg and Arvid Ekblom and Ludwig Hedlund and August Lidfeldt},
  journal={2021 IEEE International Conference on Software Testing, Verification and Validation Workshops (ICSTW)},
  year={2021},
  pages={175-181}
}
Machine Learning (ML) is a fundamental part of modern perception systems. In the last decade, the performance of computer vision using trained deep neural networks has outperformed previous approaches based on careful feature engineering. However, the opaqueness of large ML models is a substantial impediment for critical applications such as in the automotive context. As a remedy, Gradient-weighted Class Activation Mapping (Grad-CAM) has been proposed to provide visual explanations of model… 

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