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About

Peichao Cong is a researcher at the forefront of agricultural robotics and intelligent computer vision, with a focus on deep learning-based perception systems for autonomous robotic applications. His work spans two interconnected domains: precision agriculture and mobile robot navigation, making meaningful contributions to both fields through innovative adaptations of state-of-the-art detection and mapping frameworks. In agricultural AI, Cong has developed specialized models for detecting and segmenting crops under challenging real-world conditions. His MYOLO framework for shiitake mushroom detection (35 citations) and citrus tree crown segmentation system (20 citations) demonstrate his ability to engineer lightweight yet accurate solutions tailored for harvesting and spraying robots operating in complex field environments. His more recent TQVGModel further advances tomato quality grading through precise instance segmentation. Equally notable is Cong's contributions to dynamic visual SLAM, where his SEG-SLAM (27 citations) and YDD-SLAM (15 citations) systems address the longstanding challenge of accurate robot localization in environments populated by moving objects, integrating semantic understanding with geometric reasoning. With nearly 100 citations across his published work, Cong's research represents a significant bridge between agricultural automation and robust robotic perception, offering practical tools that advance the capabilities of next-generation farming and navigation systems.