Steven Lawrence Fernandes

Sahyadri Hospital, University of Alabama at Birmingham

Papers

Total Citations

135

H-Index

About

Steven Lawrence Fernandes is a leading researcher in deep learning and medical image analysis, whose work bridges artificial intelligence and clinical diagnostics. His most influential contribution, "Appearance based pedestrians’ gender recognition by employing stacked auto encoders in deep learning" (2018), has garnered 99 citations, establishing a foundational approach for automated gender classification in surveillance and human-computer interaction. This work showcases his expertise in leveraging stacked autoencoders to extract robust features from visual data, advancing the field of appearance-based recognition. Fernandes has also made significant strides in healthcare through his edited volume "Computer Aided Intervention and Diagnostics in Clinical and Medical Images" (2019, 36 citations), which synthesizes cutting-edge methods for computer-aided diagnosis, from tumor detection to organ segmentation. His research consistently demonstrates how deep learning architectures can solve real-world challenges, particularly in pedestrian analysis and medical imaging. With a focus on translational impact, Fernandes’ work continues to inspire new applications in autonomous systems and clinical decision support, making him a pivotal figure in the intersection of AI and practical problem-solving.