Peipu An

Papers

Total Citations

H-Index

About

Peipu An is a researcher at the forefront of agricultural artificial intelligence, with a primary focus on computer vision and deep learning for precision farming. His most significant contribution lies in advancing weed detection and identification in complex field environments, a critical challenge for sustainable agriculture. In his highly cited 2023 work, "Weed detection with Improved Yolov 7," An introduced an enhanced YOLOv7 model that leverages online data augmentation to improve feature extraction, fusion, and point judgment for weed imagery. This work, which has garnered 13 citations, demonstrates his ability to adapt state-of-the-art object detection architectures for real-world agricultural problems, achieving robust performance against variable lighting, occlusions, and diverse weed species. By tackling the difficult task of distinguishing crops from weeds in unstructured field backgrounds, An’s research directly supports the development of intelligent weeding systems, reducing herbicide use and labor costs. His work is notable for its practical impact, bridging the gap between cutting-edge AI and on-the-ground farming needs, and positions him as a rising innovator in the intersection of deep learning and agri-tech.