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Use of multispectral satellite images for the vegetation monitoring in the ecuadorian amazon using a u-net network in areas of industrial oil activity-infrared spectrum were analyzed by a semantic segmentation algorithm developed by labeling each pixel of the images
Image Segmentation Approaches Applied for the Earth's Surface are considered. The features of vegetation indices usage for data segmentation by satellite images are considered
A new approach of recognition of ellipsoidal micro- and nanoparticles on AFM images and determination of their sizes is based on image segmentation and the surface approximation by ellipsoids. In addition to the comparative
A generalization of segmentation methods of quantiles and modes to the case of several imagesThe problem of segmentation by several images is considered for fragments of a scene containing a
COMBINED SEGMENTATION METHOD APPLICATION FOR THE EARTH REMOTE SENSINGMULTI-SPECTRAL IMAGES RECOGNITIONThe paper is devoted to the technology of multispectral aerospace images segmentation obtained
RMNET: A Residual and Multi-scale Feature Fusion Network For High-resolution Image Semantic SegmentationHigh-resolution remote sensing images have high
clarity and provide signifi cant support for urban
A fully seeded region growing algorithm by wave propagationA fully automatic seeded region growing algorithm for image segmentation based on quasi
Image Semantic Segmentation Based on High-Resolution Networks for Monitoring Agricultural Vegetation spatial resolutions was considered. Proposed approach is based on a semantic segmentation using
Comparison of Different Convolutional Neural Network Architectures for Satellite Image Segmentation". Segmentation of satellite images has found application at urban planning, forest management, climate modelling
Using NVIDIA multicore graphics processors in image decoding, segmentation, and correction of the segmentation of zones of interest by images of locally homogeneous scenes
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