Tianjun Liu - Chines.. Now
: His technical work includes "Deep Learning in Food Image Recognition," exploring multi-branch structures for high-accuracy feature extraction.
Tianjun Liu, associated with Northwest A&F University , specializes in the intersection of traditional agricultural production and modern digital factor markets. Tianjun Liu - Chines..
: His research includes the ED-DenseNet model, which enhances deep feature extraction through multi-branch structures and ECA attention mechanisms, achieving a 97.82% recognition accuracy in gas-liquid flow patterns. : His technical work includes "Deep Learning in
: He has proposed urban big data classification methods using lightweight deep learning (LWT-DL) to improve the security and efficiency of smart city construction. : He has proposed urban big data classification
Liu's work supports the Chinese government’s strategic goal of making data a "factor of production". His findings emphasize that while China may lag in some innovation areas, it is rapidly catching up by applying massive scale and specialized AI models to traditional sectors like and rural agriculture.
: He investigates how e-commerce adoption impacts selling prices for apple farmers, finding that digital platforms increase market flexibility and benefit smaller, less-educated rural households significantly.