2 citations · 2 across the 5 of their papers we have counts for
3 papers · 1 filter
Explainable Supervised Domain Adaptation
Vidhya Kamakshi, Narayanan C Krishnan
Domain adaptation techniques have contributed to the success of deep learning. Leveraging knowledge from an auxiliary source domain for learning in labeled data-scarce target domai…
Evaluation of Saliency-based Explainability Method
Sam Zabdiel Sunder Samuel, Vidhya Kamakshi, Namrata Lodhi +1
A particular class of Explainable AI (XAI) methods provide saliency maps to highlight part of the image a Convolutional Neural Network (CNN) model looks at to classify the image as…
MACE: Model Agnostic Concept Extractor for Explaining Image Classification Networks
Ashish Kumar, Karan Sehgal, Prerna Garg +2
Deep convolutional networks have been quite successful at various image classification tasks. The current methods to explain the predictions of a pre-trained model rely on gradient…