Pyramid of Spatial Relatons for Scene-Level Land Use Classification

By Shizhi Chen, Yingli Tian. 2015

206 citations recorded by the source corpus.

Subfields: Computer Vision and Pattern Recognition, Geography, Planning and Development

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Citations in the corpus

Remote Sensing Image Scene Classification: Benchmark and State of the Art (2017, neutral): “dataset is the most popular and has been widely used for the task of remote sensing image scene classification and retrieval [8, 10, 11, 14-16, 18-20, 24, 26, 28-30, 36, 38, 53, 55, 59, 61, 62, 81, 82, 84-98].”
Training Deep Convolutional Neural Networks for Land–Cover Classification of High-Resolution Imagery (2017, methodology): “A variety of other features have also been used (see [4]–[6]), each with their respective advantages and drawbacks.”
Multiview Deep Learning for Land-Use Classification (2015, unknown): “2015 Pyramid of spatial relatons [6] 89.”
Convolutional Neural Network Based Automatic Object Detection on Aerial Images (2016, background): “Descriptive characteristics of low-level local features are more efficiently used with the combination of their spatial properties, so both local features and their position in the image are taken into consideration when the final descriptor is calculated [7]–[10].”
Transferring Deep Convolutional Neural Networks for the Scene Classification of High-Resolution Remote Sensing Imagery (2015, methodology): “[13] proposed a translation and rotation-invariant pyramid-of-spatial-relations (PSR) model to describe both relative and absolute spatial relationships of local features; Zhao et al.”
Remote Sensing Image Scene Classification Using Multi-Scale Completed Local Binary Patterns and Fisher Vectors (2016, unknown): “8 Pyramid-of-Spatial-Relatons (PSR) [36] 89.”
Tree2Vector: Learning a Vectorial Representation for Tree-Structured Data (2018, unknown): “nizing natural scene categories and objects [19]–[21].”
Semantic Annotation of High-Resolution Satellite Images via Weakly Supervised Learning (2016, background): “In recent years, the bag of visual words (BOVW) model [28] has successfully served as an intermediate feature representation for land-use classification [9], [10], [29]–[32].”
AID: A Benchmark Data Set for Performance Evaluation of Aerial Scene Classification (2016, methodology): “The BoVW model and its variants are widely used in scene classification [13], [14], [23], [24], [26], [29]–[31], [59], [86].”
Gabor-Filtering-Based Completed Local Binary Patterns for Land-Use Scene Classification (2015, methodology): “To overcome this limitation, a pyramid-ofspatial-relatons (PSR) model was proposed in [6] to capture both absolute and relative spatial relationships of local features.”