5 citations · 15 across the 22 of their papers we have counts for
22 papers
CogRad: A Cognitively-Inspired Multi-Agent Framework for Radiology Report Generation
Saif Ur Rehman Khan, Hasaan Maqsood, Sebastian Vollmer +2
Automated radiology report generation (RRG) can ease radiologist workload, yet most existing systems produce a report in a single forward pass, with no mechanism to check a claim a…
GTA-Net: Cooperative Game Theory for Vision-Language Alignment in Chest X-Ray Report Generation
Saif ur Rehman Khan, Imad Ahmed Waqar, Sebastian Vollmer +2
Automated chest X-ray report generation requires precise cross-modal grounding to ensure clinically reliable descriptions. However, existing vision-language models rely on implicit…
GC-MoE: Genomics-Guided Cell-Type-Specific Mixture of Experts for Histology-Based Single-Cell Spatial Transcriptomics
Kaito Shiku, Ahtisham Fazeel Abbasi, Ryoma Bise +4
Histology-based single-cell spatial transcriptomics (ST) estimation aims to predict gene expression for individual cells from histopathological images and cell locations, reducing…
SolarFCD: A Large-Scale Dataset and Benchmark for Solar Fault Classification in Photovoltaic Systems
Misbah Ijaz, Saif Ur Rehman Khan, Abd Ur Rehman +4
The increasing global deployment of solar photovoltaic (PV) systems needs robust, scalable, and automated inspection technologies capable of detecting a wide range of panel flaws u…
EyeBrain: Left and Right Brain Lateralization Activity Classification Through Pupil Diameter and Fixation Duration
Ko Watanabe, Pooja Pol, Nicolas Großmann +2
The relationship between brain lateralization and cognitive functions is well-documented. The left hemisphere primarily handles tasks such as language and arithmetic, while the rig…
MS-SSE-Net: A Multi-Scale Spatial Squeeze-and-Excitation Network for Structural Damage Detection in Civil and Geotechnical Engineering
Saif ur Rehman Khan, Imad Ahmed Waqar, Arooj Zaib +4
Structural damage detection is essential for maintaining the safety and reliability of civil infrastructure. However, accurately identifying different types of structural damage fr…
A Large-Scale Comparative Analysis of Imputation Methods for Single-Cell RNA Sequencing Data
Yuichiro Iwashita, Ahtisham Fazeel Abbasi, Koichi Kise +2
Background: Single-cell RNA sequencing (scRNA-seq) enables gene expression profiling at cellular resolution but is inherently affected by sparsity caused by dropout events, where e…
Automated Diabetic Screening via Anterior Segment Ocular Imaging: A Deep Learning and Explainable AI Approach
Hasaan Maqsood, Saif Ur Rehman Khan, Sebastian Vollmer +2
Diabetic retinopathy screening traditionally relies on fundus photography, requiring specialized equipment and expertise often unavailable in primary care and resource limited sett…
StructDamage:A Large Scale Unified Crack and Surface Defect Dataset for Robust Structural Damage Detection
Misbah Ijaz, Saif Ur Rehman Khan, Abd Ur Rehman +3
Automated detection and classification of structural cracks and surface defects is a critical challenge in civil engineering, infrastructure maintenance, and heritage preservation.…
GlobalWasteData: A Large-Scale, Integrated Dataset for Robust Waste Classification and Environmental Monitoring
Misbah Ijaz, Saif Ur Rehman Khan, Abd Ur Rehman +4
The growing amount of waste is a problem for the environment that requires efficient sorting techniques for various kinds of waste. An automated waste classification system is used…
Dynamic Weight Adjustment for Knowledge Distillation: Leveraging Vision Transformer for High-Accuracy Lung Cancer Detection and Real-Time Deployment
Saif Ur Rehman Khan, Muhammad Nabeel Asim, Sebastian Vollmer +1
This paper presents the FuzzyDistillViT-MobileNet model, a novel approach for lung cancer (LC) classification, leveraging dynamic fuzzy logic-driven knowledge distillation (KD) to…
FloraSyntropy-Net: Scalable Deep Learning with Novel FloraSyntropy Archive for Large-Scale Plant Disease Diagnosis
Saif Ur Rehman Khan, Muhammad Nabeel Asim, Sebastian Vollmer +1
Early diagnosis of plant diseases is critical for global food safety, yet most AI solutions lack the generalization required for real-world agricultural diversity. These models are…
FOLC-Net: A Federated-Optimized Lightweight Architecture for Enhanced MRI Disease Diagnosis across Axial, Coronal, and Sagittal Views
Saif Ur Rehman Khan, Muhammad Nabeel Asim, Sebastian Vollmer +1
The framework is designed to improve performance in the analysis of combined as well as single anatomical perspectives for MRI disease diagnosis. It specifically addresses the perf…
The Evolution of Natural Language Processing: How Prompt Optimization and Language Models are Shaping the Future
Summra Saleem, Muhammad Nabeel Asim, Shaista Zulfiqar +1
Large Language Models (LLMs) have revolutionized the field of Natural Language Processing (NLP) by automating traditional labor-intensive tasks and consequently accelerated the dev…
FREQuency ATTribution: benchmarking frequency-based occlusion for time series data
Dominique Mercier, Andreas Dengel, Sheraz Ahmed
Deep neural networks are among the most successful algorithms in terms of performance and scalability across different domains. However, since these networks are black boxes, their…
Enhanced Urdu Intent Detection with Large Language Models and Prototype-Informed Predictive Pipelines
Faiza Hassan, Summra Saleem, Kashif Javed +3
Multifarious intent detection predictors are developed for different languages, including English, Chinese and French, however, the field remains underdeveloped for Urdu, the 10th…
iBitter-Stack: A Multi-Representation Ensemble Learning Model for Accurate Bitter Peptide Identification
Sarfraz Ahmad, Momina Ahsan, Muhammad Nabeel Asim +2
The identification of bitter peptides is crucial in various domains, including food science, drug discovery, and biochemical research. These peptides not only contribute to the und…
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-…
Temperature-Driven Robust Disease Detection in Brain and Gastrointestinal Disorders via Context-Aware Adaptive Knowledge Distillation
Saif Ur Rehman Khan, Muhammad Nabeel Asim, Sebastian Vollmer +1
Medical disease prediction, particularly through imaging, remains a challenging task due to the complexity and variability of medical data, including noise, ambiguity, and differin…
AI-Driven Diabetic Retinopathy Diagnosis Enhancement through Image Processing and Salp Swarm Algorithm-Optimized Ensemble Network
Saif Ur Rehman Khan, Muhammad Nabeel Asim, Sebastian Vollmer +1
Diabetic retinopathy is a leading cause of blindness in diabetic patients and early detection plays a crucial role in preventing vision loss. Traditional diagnostic methods are oft…
PassionNet: An Innovative Framework for Duplicate and Conflicting Requirements Identification
Summra Saleem, Muhammad Nabeel Asim, Andreas Dengel
Early detection and resolution of duplicate and conflicting requirements can significantly enhance project efficiency and overall software quality. Researchers have developed vario…
Generative Language Models Potential for Requirement Engineering Applications: Insights into Current Strengths and Limitations
Summra Saleem, Muhammad Nabeel Asim, Ludger Van Elst +1
Traditional language models have been extensively evaluated for software engineering domain, however the potential of ChatGPT and Gemini have not been fully explored. To fulfill th…