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Работы, на которые ссылается эта работа
Работ: 52
Работа: Improved Agricultural Field Segmentation in Satellite Imagery Using TL-ResUNet Architecture
Sentinel-2: ESA's Optical High-Resolution Mission for GMES Operational Services
Matthias Drusch, Umberto Del Bello, Stefane Carlier +12
Статья2012Цитирований: 5ABIPerspectives of deep learning based satellite imagery analysis and efficient training of the U-Net architecture for land-use classification
Temurbek Kuchkorov, Sh. N. Urmanov, Khabibullo Nosirov +1
СтатьяRemote Sensing and Land UseDevelopments of Artificial Intelligence Technologies in Computation and Robotics2020Цитирований: 5ABIDeepGlobe 2018: A Challenge to Parse the Earth through Satellite Images
İlke Demir, Krzysztof Koperski, David Lindenbaum +6
Статья2018Цитирований: 3ABIDense Fusion Classmate Network for Land Cover Classification
Chao Tian, Cong Li, Jianping Shi
Статья2018Цитирований: 2ABIDeep Aggregation Net for Land Cover Classification
Tzu-Sheng Kuo, Keng-Sen Tseng, Jiawei Yan +2
Статья2018Цитирований: 2ABIImproving land cover segmentation across satellites using domain adaptation
Статья2021Цитирований: 2ABI