119 citations · 845 across the 65 of their papers we have counts for
18 papers · 1 filter
LD-ViCE: Latent Diffusion Model for Video Counterfactual Explanations
Payal Varshney, Adriano Lucieri, Christoph Balada +2
Video-based AI systems are increasingly adopted in safety-critical domains such as autonomous driving and healthcare. However, interpreting their decisions remains challenging due…
DocVCE: Diffusion-based Visual Counterfactual Explanations for Document Image Classification
Saifullah Saifullah, Stefan Agne, Andreas Dengel +1
As black-box AI-driven decision-making systems become increasingly widespread in modern document processing workflows, improving their transparency and reliability has become criti…
Discovering Concept Directions from Diffusion-based Counterfactuals via Latent Clustering
Payal Varshney, Adriano Lucieri, Christoph Balada +2
Concept-based explanations have emerged as an effective approach within Explainable Artificial Intelligence, enabling interpretable insights by aligning model decisions with human-…
Deep Learning for Cardiovascular Risk Assessment: Proxy Features from Carotid Sonography as Predictors of Arterial Damage
Christoph Balada, Aida Romano-Martinez, Vincent ten Cate +9
In this study, hypertension is utilized as an indicator of individual vascular damage. This damage can be identified through machine learning techniques, providing an early risk ma…
WordVIS: A Color Worth A Thousand Words
Umar Khan, Saifullah, Stefan Agne +2
Document classification is considered a critical element in automated document processing systems. In recent years multi-modal approaches have become increasingly popular for docum…
Latent Diffusion for Guided Document Table Generation
Syed Jawwad Haider Hamdani, Saifullah Saifullah, Stefan Agne +2
Obtaining annotated table structure data for complex tables is a challenging task due to the inherent diversity and complexity of real-world document layouts. The scarcity of publi…
DocXplain: A Novel Model-Agnostic Explainability Method for Document Image Classification
Saifullah Saifullah, Stefan Agne, Andreas Dengel +1
Deep learning (DL) has revolutionized the field of document image analysis, showcasing superhuman performance across a diverse set of tasks. However, the inherent black-box nature…
Revisiting the Shape-Bias of Deep Learning for Dermoscopic Skin Lesion Classification
Adriano Lucieri, Fabian Schmeisser, Christoph Peter Balada +3
It is generally believed that the human visual system is biased towards the recognition of shapes rather than textures. This assumption has led to a growing body of work aiming to…
Deep Learning Based Decision Support for Medicine -- A Case Study on Skin Cancer Diagnosis
Adriano Lucieri, Andreas Dengel, Sheraz Ahmed
Early detection of skin cancers like melanoma is crucial to ensure high chances of survival for patients. Clinical application of Deep Learning (DL)-based Decision Support Systems…
Going Beyond Classification Accuracy Metrics in Model Compression
Vinu Joseph, Shoaib Ahmed Siddiqui, Aditya Bhaskara +5
With the rise in edge-computing devices, there has been an increasing demand to deploy energy and resource-efficient models. A large body of research has been devoted to developing…
Combining Fine- and Coarse-Grained Classifiers for Diabetic Retinopathy Detection
Muhammad Naseer Bajwa, Yoshinobu Taniguchi, Muhammad Imran Malik +3
Visual artefacts of early diabetic retinopathy in retinal fundus images are usually small in size, inconspicuous, and scattered all over retina. Detecting diabetic retinopathy requ…
Two-stage framework for optic disc localization and glaucoma classification in retinal fundus images using deep learning
Muhammad Naseer Bajwa, Muhammad Imran Malik, Shoaib Ahmed Siddiqui +4
With the advancement of powerful image processing and machine learning techniques, CAD has become ever more prevalent in all fields of medicine including ophthalmology. Since optic…
A Hybrid Approach and Unified Framework for Bibliographic Reference Extraction
Syed Tahseen Raza Rizvi, Andreas Dengel, Sheraz Ahmed
Publications are an integral part in a scientific community. Bibliographic reference extraction from scientific publication is a challenging task due to diversity in referencing st…
Attributes' Importance for Zero-Shot Pose-Classification Based on Wearable Sensors
Hiroki Ohashi, Mohammad Al-Naser, Sheraz Ahmed +3
This paper presents a simple yet effective method for improving the performance of zero-shot learning (ZSL). ZSL classifies instances of unseen classes, from which no training data…
Cutting the Error by Half: Investigation of Very Deep CNN and Advanced Training Strategies for Document Image Classification
Muhammad Zeshan Afzal, Andreas Kölsch, Sheraz Ahmed +1
We present an exhaustive investigation of recent Deep Learning architectures, algorithms, and strategies for the task of document image classification to finally reduce the error b…
TAC-GAN - Text Conditioned Auxiliary Classifier Generative Adversarial Network
Ayushman Dash, John Cristian Borges Gamboa, Sheraz Ahmed +2
In this work, we present the Text Conditioned Auxiliary Classifier Generative Adversarial Network, (TAC-GAN) a text to image Generative Adversarial Network (GAN) for synthesizing i…
Judging a Book By its Cover
Brian Kenji Iwana, Syed Tahseen Raza Rizvi, Sheraz Ahmed +2
Book covers communicate information to potential readers, but can that same information be learned by computers? We propose using a deep Convolutional Neural Network (CNN) to predi…
A Generic Method for Automatic Ground Truth Generation of Camera-captured Documents
Sheraz Ahmed, Muhammad Imran Malik, Muhammad Zeshan Afzal +4
The contribution of this paper is fourfold. The first contribution is a novel, generic method for automatic ground truth generation of camera-captured document images (books, magaz…