Dongdong Peng
Papers
1
Total Citations
15
H-Index
1
About
Dr. Dongdong Peng is a leading researcher in agricultural robotics and computer vision, with a primary focus on precision viticulture. His work centers on developing advanced deep learning models for the automated detection and instance segmentation of fruit in complex orchard environments. Dr. Peng’s major contribution is the creation of an improved Mask R-CNN architecture, which overcomes critical challenges like variable lighting, fruit occlusion, and overlapping clusters. His most cited paper, "Detection and Instance Segmentation of Grape Clusters in Orchard Environments Using an Improved Mask R-CNN Model" (2024, 15 citations), demonstrates a robust solution for accurately segmenting grape clusters and identifying different varieties. This innovation directly supports yield estimation, growth monitoring, and the development of efficient mechanical harvesting systems. By bridging the gap between computer vision and agricultural engineering, Dr. Peng’s work provides orchard staff with powerful tools for data-driven management, significantly advancing the automation and intelligence of modern farming practices.
Research Focus
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Top Papers
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