Yazeed Alkharijah

Imam Mohammad ibn Saud Islamic University

Papers

Total Citations

H-Index

About

Yazeed Alkharijah is a rising researcher in computer vision, with a focused interest in egocentric perception and the integration of transformer architectures with convolutional neural networks. His most notable contribution is the development of **EgoVision**, a novel hybrid model combining YOLO (You Only Look Once) with Vision Transformers (ViT) to address the unique challenges of object recognition from first-person perspectives. This work tackles critical issues such as occlusion, motion blur, and viewpoint variability that plague egocentric vision systems, making it highly relevant for applications in assistive technologies, augmented reality, and human-computer interaction. While his citation count is still growing, his early work demonstrates significant promise in pushing the boundaries of how machines perceive the world from a human-centric viewpoint. Alkharijah’s research sits at the intersection of real-time object detection and advanced attention mechanisms, positioning him as an emerging voice in the field. His efforts contribute to making AI systems more intuitive and context-aware, particularly for wearable and mobile platforms.