Kwan Liang Hong

Papers

Total Citations

H-Index

About

Kwan Liang Hong is a researcher at the forefront of applying artificial intelligence to agricultural science, with a primary focus on fruit classification and quality assessment. His most cited work, "Classification of Mango Species and Ripeness Using Feature Extraction with an Artificial Neural Network" (2024), demonstrates his expertise in combining computer vision and machine learning to solve real-world agricultural challenges. By developing a feature extraction method integrated with an artificial neural network, Hong has contributed to non-destructive, automated systems for identifying mango species and determining ripeness—a critical innovation for post-harvest processing and supply chain efficiency. While his citation count is still growing, this foundational paper signals his potential to influence precision agriculture and food technology. Hong’s work sits at the intersection of deep learning, image processing, and horticulture, offering practical tools for farmers and distributors. As a rising voice in AI-driven agriculture, his research paves the way for smarter, data-driven approaches to crop management and quality control, with implications for reducing food waste and improving yield assessment.