Hao Ma

Henan University of Science and Technology, Dalian University of Technology

Papers

Total Citations

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About

Hao Ma is an emerging researcher whose work sits at the intersection of agricultural automation, computer vision, and intelligent robotics. Ma's most significant contributions center on developing lightweight deep learning models for precision agriculture, particularly focused on the automated detection and harvesting of *Agaricus bisporus* (common mushrooms). His flagship work, FES-YOLOv5s, introduced an innovative adaptation of the YOLOv5s architecture to tackle real-world challenges such as mushroom adhesion and occlusion in complex growing environments, earning 7 citations since its 2024 publication. Building directly on this foundation, Ma extended the model into a practical, machine vision-based intelligent harvesting device, addressing long-standing inefficiencies in manual mushroom harvesting and accumulating 5 citations within a year of publication. Beyond agriculture, Ma has also explored human-robot interaction, proposing a novel movement-supported HRI framework for humanoid bipedal robots that accounts for lower-limb locomotion during interaction — a meaningful departure from conventional static-assumption models. Though still early in his career, Ma's research demonstrates a consistent drive to bridge cutting-edge machine learning with tangible real-world agricultural and robotic applications.