Recently, Professor Antonio J. Plaza, Chairman of the IEEE Geoscience and Remote Sensing Society (IEEE GRSS) Paper Awards Committee sent a congratulatory message congratulating the paper co-written by Professor Cheng Gong, Professor Han Junwei, and others from the Brain and Artificial Intelligence Research Team of the School of Automation Engineering winning the IEEE GRSS Highest Impact Paper Award in 2023. This award is established by the IEEE Geoscience and Remote Sensing Society and is one of the most influential paper awards in the field of remote sensing. It is presented once a year and selected from over 12,000 papers. The aim is to reward the academic papers that have been published in three SCI journals organized by IEEE GRSS (IEEE TGRS/JSTARS/GRSL) and have received the highest number of citations and impact over the past 5 years. Northwestern Polytechnical University is the sole signatory of this paper.
This is the third time in the past three years that the research team has won a top international academic award. Paper [2] won the Most Influential Paper Award of the IEEE Geoscience and Remote Sensing Society in 2021 (the first award for independent work by a Chinese research institution), and paper [3] won the Best Paper Award of 2021 (the second award for independent work by a Chinese research institution in 30 years) from the top international journal in the multimedia field, IEEE TCSVT.
Attachment: Information on Award-winning Papers
[1]. G. Cheng, C. Yang, X. Yao, L. Guo, J. Han*. When deep learning meets metric learning: remote sensing image scene classification via learning discriminative CNNs. IEEE Transactions on Geoscience and Remote Sensing (TGRS), 2018.
[2]. G. Cheng, P. Zhou, J. Han*. Learning rotation-invariant convolutional neural networks for object detection in VHR optical remote sensing images. IEEE Transactions on Geoscience and Remote Sensing (TGRS), 2016.
[3]. J. Han, G. Cheng*, Z. Li, D. Zhang*. A Unified Metric Learning-Based Framework for Co-Saliency Detection. IEEE Transactions on Circuits and Systems for Video Technology (TCSVT), 2018.
Source: School of Automation
Translator: Ma Le
