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Found 5 papers, 3 papers with code
Enhancing the Fairness and Performance of Edge Cameras with Explainable AI
The rising use of Artificial Intelligence (AI) in human detection on Edge camera systems has led to accurate but complex models, challenging to interpret and debug.
A Novel Explainable Artificial Intelligence Model in Image Classification problem
Therefore, many algorithms are studied for the purpose of explaining AI models, especially those in the problem of image classification in the field of computer vision such as LIME, CAM, GradCAM.
G-CAME: Gaussian-Class Activation Mapping Explainer for Object Detectors
Nowadays, deep neural networks for object detection in images are very prevalent.
Towards Better Explanations for Object Detection
Recent advances in Artificial Intelligence (AI) technology have promoted their use in almost every field.
Towards Trust of Explainable AI in Thyroid Nodule Diagnosis
In this paper, we apply state-of-the-art eXplainable artificial intelligence (XAI) methods to explain the prediction of the black-box AI models in the thyroid nodule diagnosis application.
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