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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…
A Multimodal Lightweight Approach to Fault Diagnosis of Induction Motors in High-Dimensional Dataset
Usman Ali
An accurate AI-based diagnostic system for induction motors (IMs) holds the potential to enhance proactive maintenance, mitigating unplanned downtime and curbing overall maintenanc…