Xiaosong An

Papers

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About

Xiaosong An is a leading researcher in agricultural automation and deep learning-based vision systems, with a primary focus on intelligent fruit sorting technologies. Their major contributions lie in developing real-time, high-accuracy vision systems that replace manual, time-consuming citrus sorting processes. An’s most-cited work, “A Deep Learning-Based Vision System Combining Detection and Tracking for Fast On-Line Citrus Sorting” (2021, 70 citations), introduces an integrated deep learning framework that simultaneously detects and tracks defective fruits on a processing line, dramatically improving sorting speed and cost-efficiency. Building on this, their 2022 study “A Vision System Based on CNN-LSTM for Robotic Citrus Sorting” (23 citations) advances the field by pairing convolutional and recurrent neural networks with robotic grippers, enabling seamless, real-time sorting adaptable to diverse citrus varieties. These innovations address critical bottlenecks in post-harvest processing, offering scalable solutions that enhance accuracy while reducing labor dependency. An’s work is pivotal for students and researchers exploring the intersection of computer vision, robotics, and agricultural engineering, demonstrating how deep learning can transform traditional food processing into an automated, intelligent industry.