Poster: Explanations via Minimal regions and Semantic Correspondence
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The objective of this poster presentation was to articulate our research endeavors in the realm of Explainable Artificial Intelligence to industry professionals, and to illustrate potential applications thereof. The central premise was to underscore the importance of generating human-comprehensible and interpretable explanations through sub-symbolic representations of images, such as components of an object within an image, which serve as inputs to a Deep Neural Network (DNN) model.