Syed Irtaza Haider

Papers

Total Citations

H-Index

About

Syed Irtaza Haider is an emerging researcher whose work sits at the intersection of deep learning, human-computer interaction, and agricultural technology. His most cited paper, "Deep Learning Approach for Hand Gesture Recognition: Applications in Deaf Communication and Healthcare" (2024, 12 citations), introduces a novel framework for hand gesture recognition (HGRoc) that bridges communication gaps for the deaf community and enhances healthcare interfaces. By leveraging convolutional neural networks, Haider’s approach achieves high accuracy in real-time gesture interpretation, directly contributing to more inclusive and error-free human-computer interaction. His earlier work, a correction to "An Optimized Method for Segmentation and Classification of Apple Diseases Based on Strong Correlation and Genetic Algorithm Based Feature Selection" (2020, 3 citations), underscores his commitment to precision in agricultural AI—specifically, improving disease detection in crops through optimized feature selection and segmentation. Though early in his career, Haider’s research demonstrates a clear focus on applying deep learning to socially impactful domains, from assistive communication to smart farming. His growing citation record reflects the relevance of his contributions, positioning him as a promising voice in applied machine learning.