Papers
1
Total Citations
4
H-Index
1
About
Fei Pan is a researcher at the forefront of agricultural robotics and intelligent vision systems, with a focused expertise in real-time fruit damage detection and automated sorting. Their most notable contribution is the development of FFTCA (Fast Fourier Transform-based Channel Attention), a novel feature fusion mechanism that dramatically accelerates the classification of apple damage for robotic sorting applications. This work, published in 2024 and already garnering 4 citations, demonstrates Pan’s ability to bridge advanced signal processing with practical agricultural automation. By integrating Fast Fourier Transform into attention mechanisms, Pan has enabled robots to rapidly and accurately identify bruised or defective apples, addressing a critical bottleneck in post-harvest processing. This innovation holds significant promise for reducing food waste and improving efficiency in the agricultural supply chain. Pan’s research sits at the intersection of computer vision, deep learning, and robotics, offering scalable solutions for real-time quality control. As their work gains traction, Fei Pan is emerging as a key voice in the growing field of precision agriculture and intelligent sorting systems.
Research Focus
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Top Papers
- 1