| PatternNet: A benchmark dataset for performance evaluation of remote sensing image retrieval W Zhou, S Newsam, C Li, Z Shao ISPRS journal of photogrammetry and remote sensing 145, 197-209, 2018 | 530 | 2018 |
| GANMcC: A generative adversarial network with multiclassification constraints for infrared and visible image fusion J Ma, H Zhang, Z Shao, P Liang, H Xu IEEE Transactions on Instrumentation and Measurement 70, 1-14, 2020 | 522 | 2020 |
| A review of multimodal image matching: Methods and applications X Jiang, J Ma, G Xiao, Z Shao, X Guo Information Fusion 73, 22-71, 2021 | 421 | 2021 |
| Seaships: A large-scale precisely annotated dataset for ship detection Z Shao, W Wu, Z Wang, W Du, C Li IEEE transactions on multimedia 20 (10), 2593-2604, 2018 | 390 | 2018 |
| Remote sensing image fusion with deep convolutional neural network Z Shao, J Cai IEEE journal of selected topics in applied earth observations and remote …, 2018 | 340 | 2018 |
| Smart city based on digital twins L Deren, Y Wenbo, S Zhenfeng Computational Urban Science 1, 1-11, 2021 | 276 | 2021 |
| Urban remote sensing Q Weng, DA Quattrochi CRC press, 2006 | 266 | 2006 |
| Urban sprawl and its impact on sustainable urban development: a combination of remote sensing and social media data Z Shao, NS Sumari, A Portnov, F Ujoh, W Musakwa, PJ Mandela Geo-Spatial Information Science 24 (2), 241-255, 2021 | 262 | 2021 |
| MFF-GAN: An unsupervised generative adversarial network with adaptive and gradient joint constraints for multi-focus image fusion H Zhang, Z Le, Z Shao, H Xu, J Ma Information Fusion 66, 40-53, 2021 | 253 | 2021 |
| ‘Big data’for pedestrian volume: Exploring the use of Google Street View images for pedestrian counts L Yin, Q Cheng, Z Wang, Z Shao Applied Geography 63, 337-345, 2015 | 253 | 2015 |
| Deep learning-based fusion of Landsat-8 and Sentinel-2 images for a harmonized surface reflectance product Z Shao, J Cai, P Fu, L Hu, T Liu Remote Sensing of Environment 235, 111425, 2019 | 241 | 2019 |
| Cloud detection in remote sensing images based on multiscale features-convolutional neural network Z Shao, Y Pan, C Diao, J Cai IEEE Transactions on Geoscience and Remote Sensing 57 (6), 4062-4076, 2019 | 239 | 2019 |
| BRRNet: A fully convolutional neural network for automatic building extraction from high-resolution remote sensing images Z Shao, P Tang, Z Wang, N Saleem, S Yam, C Sommai Remote Sensing 12 (6), 1050, 2020 | 227 | 2020 |
| Learning low dimensional convolutional neural networks for high-resolution remote sensing image retrieval W Zhou, S Newsam, C Li, Z Shao Remote Sensing 9 (5), 489, 2017 | 226 | 2017 |
| Remote sensing monitoring of multi-scale watersheds impermeability for urban hydrological evaluation Z Shao, H Fu, D Li, O Altan, T Cheng Remote Sensing of Environment 232, 111338, 2019 | 216 | 2019 |
| Saliency-aware convolution neural network for ship detection in surveillance video Z Shao, L Wang, Z Wang, W Du, W Wu IEEE Transactions on Circuits and Systems for Video Technology 30 (3), 781-794, 2019 | 210 | 2019 |
| Multilabel remote sensing image retrieval based on fully convolutional network Z Shao, W Zhou, X Deng, M Zhang, Q Cheng IEEE Journal of Selected Topics in Applied Earth Observations and Remote …, 2020 | 202 | 2020 |
| A comprehensive evaluation of urban sustainable development in China based on the TOPSIS-entropy method L Ding, Z Shao, H Zhang, C Xu, D Wu Sustainability 8 (8), 746, 2016 | 201 | 2016 |
| Integrated remote sensing and GIS approach using Fuzzy-AHP to delineate and identify groundwater potential zones in semi-arid Shanxi Province, China Z Shao, ME Huq, B Cai, O Altan, Y Li Environmental Modelling & Software 134, 104868, 2020 | 191 | 2020 |
| Deep learning based retrieval of forest aboveground biomass from combined LiDAR and landsat 8 data L Zhang, Z Shao, J Liu, Q Cheng Remote Sensing 11 (12), 1459, 2019 | 170 | 2019 |
Orhan AltanEm. Professor at the Istanbul Technical Universityitu.edu.tr의 이메일 확인됨