.png){kind=icon}
.png){kind=icon}
Return
ResDeepGS: A deep learning-based method for crop phenotype prediction
.png){kind=icon}
PRE
AI
DOI：10.1016/j.ymeth.2025.07.013.png)
.png){kind=icon}
Original request for help.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
• ResDeepGS: A novel deep learning model that integrates convolutional neural networks and residual structures for accurate crop phenotype prediction. • The model outperforms existing methods such as DeepGS, DNNGP, and GBLUP across multiple datasets (wheat, maize, and soybean). • The incorporation of residual structures helps mitigate over tting and enhances the generalization ability of the model, making it suitable for complex genetic datasets.
Journal
IF:
4.3
Papers:
4.8K
Citations:
2.4W