Dec 18, 2020 · In this study, a new change detection method is proposed by combining multi-scale simple linear iterative clustering-convolutional neural network (SLIC-CNN) ...
In this study, a new change detection method is proposed by combining multi-scale simple linear iterative clustering-convolutional neural network (SLIC-CNN) ...
Dec 31, 2020 · To improve the efficiency of change detection, the binary change map generated from multi-scale SLIC-CNN is used to cover the entire study area,.
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Mar 18, 2024 · This research proposes a change detection in the satellite images and land cover analysis using a Bidirectional Long Short-Term Memory (BiLSTM) model and ...
Fast and accurate land-cover classification on medium-resolution remote-sensing images using segmentation models · Land Cover Change Detection With VHR Satellite ...
Change detection with very high resolution (VHR) satellite images is of great application values when evaluating and monitoring land use changes.
We propose a Multi-Scale Fully Convolutional Network (MSFCN) with a multi-scale convolutional kernel as well as a Channel Attention Block (CAB) and a Global ...
Missing: SLIC- SCAE
In this study, we utilize very high-resolution (VHR) optical imagery with a resolution of 50 cm to improve object recognition for GEOBIA LULC classification.
Missing: SLIC- SCAE
Nov 28, 2022 · Presents the three-layer edge-fog-cloud-based satellite IoT architecture to deploy the proposed SLIC-CNN framework. •. Discusses the ...
Missing: SCAE | Show results with:SCAE
Superpixel based land cover classification of VHR satellite image combining multi-scale CNN and scale parameter estimation.
Missing: SCAE | Show results with:SCAE