Search Results for author: Adriano Lucieri

Found 9 papers, 3 papers with code

Revisiting the Shape-Bias of Deep Learning for Dermoscopic Skin Lesion Classification

1 code implementation13 Jun 2022 Adriano Lucieri, Fabian Schmeisser, Christoph Peter Balada, Shoaib Ahmed Siddiqui, Andreas Dengel, Sheraz Ahmed

Interestingly, despite deep feature extractors being inclined towards learning entangled features for skin lesion classification, individual features can still be decoded from this entangled representation.

Classification Decision Making +2

ExAID: A Multimodal Explanation Framework for Computer-Aided Diagnosis of Skin Lesions

no code implementations4 Jan 2022 Adriano Lucieri, Muhammad Naseer Bajwa, Stephan Alexander Braun, Muhammad Imran Malik, Andreas Dengel, Sheraz Ahmed

This work presents ExAID (Explainable AI for Dermatology), a novel framework for biomedical image analysis, providing multi-modal concept-based explanations consisting of easy-to-understand textual explanations supplemented by visual maps justifying the predictions.

Decision Making

Evaluating Privacy-Preserving Machine Learning in Critical Infrastructures: A Case Study on Time-Series Classification

1 code implementation29 Nov 2021 Dominique Mercier, Adriano Lucieri, Mohsin Munir, Andreas Dengel, Sheraz Ahmed

With the advent of machine learning in applications of critical infrastructure such as healthcare and energy, privacy is a growing concern in the minds of stakeholders.

BIG-bench Machine Learning Privacy Preserving +3

Deep Learning Based Decision Support for Medicine -- A Case Study on Skin Cancer Diagnosis

no code implementations2 Mar 2021 Adriano Lucieri, Andreas Dengel, Sheraz Ahmed

Moreover, the possibility to intervene and guide models in case of misbehaviour is identified as a major step towards successful deployment of AI as DL-based DSS and beyond.

Achievements and Challenges in Explaining Deep Learning based Computer-Aided Diagnosis Systems

no code implementations26 Nov 2020 Adriano Lucieri, Muhammad Naseer Bajwa, Andreas Dengel, Sheraz Ahmed

Remarkable success of modern image-based AI methods and the resulting interest in their applications in critical decision-making processes has led to a surge in efforts to make such intelligent systems transparent and explainable.

Decision Making

On Interpretability of Deep Learning based Skin Lesion Classifiers using Concept Activation Vectors

no code implementations5 May 2020 Adriano Lucieri, Muhammad Naseer Bajwa, Stephan Alexander Braun, Muhammad Imran Malik, Andreas Dengel, Sheraz Ahmed

This work aims at elucidating a deep learning based medical image classifier by verifying that the model learns and utilizes similar disease-related concepts as described and employed by dermatologists.

Decision Making Image Classification +1

Explaining AI-based Decision Support Systems using Concept Localization Maps

1 code implementation4 May 2020 Adriano Lucieri, Muhammad Naseer Bajwa, Andreas Dengel, Sheraz Ahmed

We evaluated our proposed method on SCDB as well as a real-world dataset called CelebA.

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