Foshan University - China
Author Profile
GOOGLE SCHOLAR
Summary
Xinwei He, a second-year master’s student in software engineering at foshan university, is an emerging researcher in the field of object detection with a strong inclination toward real-world applications in power electronics and automation systems. his key contribution—tgcpn: two-level grid context propagation network for 3d small object detection—showcases a blend of academic depth and practical insight. through active participation in publication, code sharing, and peer-reviewed processes, xinwei is steadily building a credible academic presence. while early in his career, his focused research direction and commitment to quality reflect significant potential for future impact.
Early academic pursuits
Xinwei he is currently a second-year master's student in software engineering at foshan university. with a foundational understanding of computational models and a growing proficiency in research methodology, xinwei began contributing to the academic domain early in postgraduate studies. the integration of power Object Detection electronics principles with intelligent object recognition marked a turning point in xinwei's academic direction. xinwei is steadily building a credible academic presence. while early in his career, his focused research direction and commitment to quality reflect significant potential for future impact.
Professional endeavors
Though still in the academic phase, xinwei he has demonstrated professional maturity through the successful development of the project titled tgcpn: two-level grid context propagation network for 3d small object detection. this work highlights the Object Detection application of computer vision within high-efficiency environments, including power electronics-based automation systems. the project underscores a capacity to work at the intersection of deep learning and real-world utility.
Contributions and research focus
Xinwei’s primary area of research is object detection, with an emphasis on small-scale 3d object identification in complex environments. the recently completed paper revision and response to peer review comments demonstrates not only technical proficiency but also academic resilience. this effort contributes meaningfully to current advancements Object Detection in image detection technologies within power electronics and robotics-based systems.
Impact and influence
Xinwei he's ongoing work is gaining attention through platforms like github and springer. by leveraging code sharing and academic publication, Xinwei is establishing a transparent and collaborative research footprint. Object Detection although citation indices are in early stages, the methodological rigor and thematic relevance suggest promising growth in academic influence, particularly in the automation sector.
Academic cites
The project has been recognized in academic channels, with a publication under a reputable journal indexed by springer. while specific citation metrics are pending, xinwei's engagement with high-impact areas such as Object Detection power electronics-driven automation systems, signal propagation, and detection architecture indicates future relevance in citations and scholarly reference.
Legacy and future contributions
Xinwei he is poised to contribute further to the fields of object detection and robotics. future plans likely include expanding research collaborations, deepening the interface between object detection and applied power electronics, and increasing journal presence. with a strong ethical foundation as expressed in the self-declaration, xinwei seeks to build a legacy of integrity, innovation, and interdisciplinary growth.
Notable Publications
Title: Tgcpn: Two-level grid context propagation network for 3D small object detection
Authors: Y. Zhou, L. Pu, X. Xu, C. Yi, X. He, Y. Zhou, Y. Xu
Journal: Pattern Analysis and Applications
Conclusion
Xinwei He exemplifies the qualities of a dedicated and innovative researcher whose early contributions are already aligning with critical technological trends like automation and power electronics-driven systems. his consistent efforts in refining research output, responding to scholarly critique, and collaborating through open platforms position him well for long-term influence. with continued mentorship and engagement, xinwei is set to evolve into a valuable contributor to the global robotics and software engineering community.