IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium 2022
DOI: 10.1109/igarss46834.2022.9884728
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A Deep Learning-Based Framework for Urban Active Population Mapping from Remote Sensing Imagery

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“…By leveraging high-level semantic information and low/middle-level features extracted from RS imagery, it becomes possible to establish evidence of the shipyard production state. Convolutional neural networks (CNNs), such as AlexNet [41][42][43], VGG [44,45], ResNet [46][47][48][49][50][51], and Inception [20,52,53], among others, can effectively derive high-level semantic information [39,[54][55][56] for extracting optical production state features from optical HRS data.…”
Section: Introductionmentioning
confidence: 99%
“…By leveraging high-level semantic information and low/middle-level features extracted from RS imagery, it becomes possible to establish evidence of the shipyard production state. Convolutional neural networks (CNNs), such as AlexNet [41][42][43], VGG [44,45], ResNet [46][47][48][49][50][51], and Inception [20,52,53], among others, can effectively derive high-level semantic information [39,[54][55][56] for extracting optical production state features from optical HRS data.…”
Section: Introductionmentioning
confidence: 99%