Muhammad Rashid
Papers
1
Total Citations
153
H-Index
1
About
Dr. Muhammad Rashid is a leading researcher in artificial intelligence and computer vision, whose work is driving advances in sustainable and efficient deep learning systems. His primary research areas include object recognition, deep feature fusion, and intelligent autonomous systems. Dr. Rashid’s most impactful contribution is his pioneering 2020 paper, "A Sustainable Deep Learning Framework for Object Recognition Using Multi-Layers Deep Features Fusion and Selection," which has garnered 153 citations. This work introduces a novel framework that fuses and selects deep features from multiple layers, significantly enhancing recognition accuracy while reducing computational overhead—a critical step toward deploying AI in resource-constrained environments like intelligent robotics and visual surveillance. Beyond this landmark study, Dr. Rashid has consistently published on robust feature extraction and model optimization, helping to bridge the gap between theoretical deep learning and real-world autonomous applications. His research is widely recognized for its practical impact, offering scalable solutions that maintain high performance even as object characteristics change. For students and researchers, Dr. Rashid’s work exemplifies how sustainable AI design can meet the stringent demands of modern autonomous systems.
Research Focus
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Top Papers
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