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Found 5 papers, 3 papers with code
Stop overkilling simple tasks with black-box models and use transparent models instead
In recent years, the employment of deep learning methods has led to several significant breakthroughs in artificial intelligence.
Fruit Ripeness Classification: a Survey
Thus, there is an arising need for automation in fruit ripeness classification.
A Theoretical Framework for AI Models Explainability with Application in Biomedicine
EXplainable Artificial Intelligence (XAI) is a vibrant research topic in the artificial intelligence community, with growing interest across methods and domains.
Evaluating the Faithfulness of Saliency-based Explanations for Deep Learning Models for Temporal Colour Constancy
The opacity of deep learning models constrains their debugging and improvement.
Cascading Convolutional Temporal Colour Constancy
We extend this architecture with different models obtained by (i) substituting the TCCNet submodules with C4, the state-of-the-art method for CCC targeting images; (ii) adding a cascading strategy to perform an iterative improvement of the estimate of the illuminant.
