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cs.CV2026
How a Model's Architecture and Performance Influences Explainability: A Study of Grad-CAM and CRAFT in CNN-Based Image Classification
Kilian Göller, Haadia Amjad, Steffen Seitz +2
Deep learning models, particularly convolutional neural networks (CNNs), are widely adopted in computer vision, yet their opaque decision-making raises concerns in high-risk applic…
cs.CV2026
Identifying Confusion Trends in Concept-based XAI for Multi-Label Classification
Haadia Amjad, Ronald Tetzlaff
Deep Neural Networks (DNNs) deployed in high-risk domains, such as healthcare and autonomous driving, must be not only accurate but also understandable to ensure user trust. In rea…
cs.CV2024
Block Induced Signature Generative Adversarial Network (BISGAN): Signature Spoofing Using GANs and Their Evaluation
Haadia Amjad, Kilian Goeller, Steffen Seitz +4
Deep learning is actively being used in biometrics to develop efficient identification and verification systems. Handwritten signatures are a common subset of biometric data for au…