How can smart agricultural equipment accurately detect pedestrians in complex scenarios?
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A study published by Associate Professor Yanfei Li’s team from Hunan Agricultural University in Frontiers of Agricultural Science and Engineering provides an innovative solution to this challenge (DOI: 10.15302/J-FASE-2025613).
A study led by Professor Hui Liu from Central South University, published in Frontiers of Agricultural Science and Engineering (DOI: 10.15302/J-FASE-2024599), introduces a hybrid deep learning model named “ICEEMDAN-LZC-BVMD-SSA-DELM”, which significantly enhances the prediction accuracy of soybean futures prices. By integrating multi-stage data preprocessing and intelligent optimization algorithms, the model addresses limitations of traditional methods in noise handling, parameter tuning, and generalization capabilities, offering new insights for risk management in agricultural financial markets.