Accelerating the Training Process of Convolutional Neural Networks for Classification by Dropping Training Samples out. - Naisen Yang; Hong Tang 002; Jianwei Yue; Xin Yang; Zhihua Xu (IGARSS, 2018)

DropBand: A Simple and Effective Method for Promoting the Scene Classification Accuracy of Convolutional Neural Networks for VHR Remote Sensing Imagery. - Naisen Yang; Hong Tang 005; Hongquan Sun; Xin Yang (IEEE Geosci. Remote. Sens. Lett., 2018)

Accelerating the Training Process of Convolutional Neural Networks for Image Classification by Dropping Training Samples Out. - Naisen Yang; Hong Tang 002; Jianwei Yue; Xin Yang; Zhihua Xu (IEEE Access, 2020)

GeoBoost: An Incremental Deep Learning Approach toward Global Mapping of Buildings from VHR Remote Sensing Images. - Naisen Yang; Hong Tang 002 (Remote. Sens., 2020)

Semantic Segmentation of Satellite Images: A Deep Learning Approach Integrated with Geospatial Hash Codes. - Naisen Yang; Hong Tang 005 (Remote. Sens., 2021)

Clarifying Relationship between PM2.5 Concentrations and Spatiotemporal Predictors Using Multi-Way Partial Dependence Plots. - Haoze Shi; Naisen Yang; Xin Yang; Hong Tang 005 (Remote. Sens., 2023)

Dynamic inference for on-orbit scene classification with the scale boosting model. - Kunyang Yang; Naisen Yang; Hong Tang (Int. J. Appl. Earth Obs. Geoinformation, 2025)