1 citations · 1 across the 7 of their papers we have counts for
8 papers
Test-Time Adaptation for Anomaly Segmentation via Topology-Aware Optimal Transport Chaining
Ali Zia, Usman Ali, Umer Ramzan +3
Deep topological data analysis (TDA) offers a principled framework for capturing structural invariants such as connectivity and cycles that persist across scales, making it a natur…
2D_3D Feature Fusion via Cross-Modal Latent Synthesis and Attention Guided Restoration for Industrial Anomaly Detection
Usman Ali, Ali Zia, Abdul Rehman +5
Industrial anomaly detection (IAD) increasingly benefits from integrating 2D and 3D data, but robust cross-modal fusion remains challenging. We propose a novel unsupervised framewo…
Split-Fuse-Transport: Annotation-Free Saliency via Dual Clustering and Optimal Transport Alignment
Muhammad Umer Ramzan, Ali Zia, Abdelwahed Khamis +3
Salient object detection (SOD) aims to segment visually prominent regions in images and serves as a foundational task for various computer vision applications. We posit that SOD ca…
Hypergraph Contrastive Sensor Fusion for Multimodal Fault Diagnosis in Induction Motors
Usman Ali, Ali Zia, Waqas Ali +4
Reliable induction motor (IM) fault diagnosis is vital for industrial safety and operational continuity, mitigating costly unplanned downtime. Conventional approaches often struggl…
An Improved Fault Diagnosis Strategy for Induction Motors Using Weighted Probability Ensemble Deep Learning
Usman Ali, Waqas Ali, Umer Ramzan
Early detection of faults in induction motors is crucial for ensuring uninterrupted operations in industrial settings. Among the various fault types encountered in induction motors…
Leveraging Deep Learning with Multi-Head Attention for Accurate Extraction of Medicine from Handwritten Prescriptions
Usman Ali, Sahil Ranmbail, Muhammad Nadeem +3
Extracting medication names from handwritten doctor prescriptions is challenging due to the wide variability in handwriting styles and prescription formats. This paper presents a r…