15 citations · 15 across the 2 of their papers we have counts for
3 papers
cs.CV2025
Leveraging counterfactual concepts for debugging and improving CNN model performance
Syed Ali Tariq, Tehseen Zia
Counterfactual explanation methods have recently received significant attention for explaining CNN-based image classifiers due to their ability to provide easily understandable exp…
cs.CV2025
Faithful Counterfactual Visual Explanations (FCVE)
Bismillah Khan, Syed Ali Tariq, Tehseen Zia +2
Deep learning models in computer vision have made remarkable progress, but their lack of transparency and interpretability remains a challenge. The development of explainable AI ca…
cs.CV2025★ 15 cited
Towards Counterfactual and Contrastive Explainability and Transparency of DCNN Image Classifiers
Syed Ali Tariq, Tehseen Zia, Mubeen Ghafoor
Explainability of deep convolutional neural networks (DCNNs) is an important research topic that tries to uncover the reasons behind a DCNN model's decisions and improve their unde…