Hybrid Convolutional Neural Networks with Reliability Guarantee
<|reference_start|>Hybrid Convolutional Neural Networks with Reliability Guarantee: Making AI safe and dependable requires the generation of dependable models and dependable execution of those models. We propose redundant execution as a well-known technique that can be used to ensure reliable execution of the AI model. This generic technique will extend the application scope of AI-accelerators that do not feature well-documented safety or dependability properties. Typical redundancy techniques incur at least double or triple the computational expense of the original. We adopt a co-design approach, integrating reliable model execution with non-reliable execution, focusing that additional computational expense only where it is strictly necessary. We describe the design, implementation and some preliminary results of a hybrid CNN.<|reference_end|>
@article{doran2024hybrid,
    title={Hybrid Convolutional Neural Networks with Reliability Guarantee},
    author={Hans Dermot Doran and Suzana Veljanovska},
    journal={arXiv preprint arXiv:2405.05146},
    year={2024},
    archivePrefix={arXiv},
    eprint={2405.05146},
    primaryClass={cs.AI}
}