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Found 4 papers, 1 papers with code
Comparison of attention models and post-hoc explanation methods for embryo stage identification: a case study
An important limitation to the development of AI-based solutions for In Vitro Fertilization (IVF) is the black-box nature of most state-of-the-art models, due to the complexity of deep learning architectures, which raises potential bias and fairness issues.
Towards deep learning-powered IVF: A large public benchmark for morphokinetic parameter prediction
An important limitation to the development of Artificial Intelligence (AI)-based solutions for In Vitro Fertilization (IVF) is the absence of a public reference benchmark to train and evaluate deep learning (DL) models.
Metrics for saliency map evaluation of deep learning explanation methods
Due to the black-box nature of deep learning models, there is a recent development of solutions for visual explanations of CNNs.
BR-NPA: A Non-Parametric High-Resolution Attention Model to improve the Interpretability of Attention
The prevalence of employing attention mechanisms has brought along concerns on the interpretability of attention distributions.
