Results 331 to 340 of about 1,087,010 (389)
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Adaptive spatiotemporal multiple sensor fusion
Optical Engineering, 2003We have developed and applied a spatiotemporal fusion framework that uses different fusion strategies across time frames (temporal fusion) as well as between sensors (spatial fusion). We have developed, at the feature level, new and different fusion strategies (additive and minmax fusion) in addition to the traditional strategies (multiplicative, min ...
Hai-Wen Chen, Teresa L. P. Olson
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Knowledge Fusion and Spatiotemporal Data Cleaning: A Review
2020 IEEE Fifth International Conference on Data Science in Cyberspace (DSC), 2020Knowledge fusion is aimed to establish the relationship between heterogeneous ontology or heterogeneous instances. Data cleaning is one of the key technologies for solving knowledge fusion problems. In this paper, we provide a brief survey of knowledge fusion and data cleaning.
Zhaoquan Gu, Mohan Li, Huchen Zhou
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Remote Sensing of Environment, 2022
Abstract Spatiotemporal image fusion is a potential way to resolve the constraint between the spatial and temporal resolutions of satellite images and has been developed rapidly in recent years. However, two key challenges related to fusion accuracy remain: a) reducing the uncertainty of image fusion caused by sensor differences and b) addressing ...
Wenzhong Shi, Dizhou Guo, Hua Zhang
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Abstract Spatiotemporal image fusion is a potential way to resolve the constraint between the spatial and temporal resolutions of satellite images and has been developed rapidly in recent years. However, two key challenges related to fusion accuracy remain: a) reducing the uncertainty of image fusion caused by sensor differences and b) addressing ...
Wenzhong Shi, Dizhou Guo, Hua Zhang
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STFRDN: a residual dense network for remote sensing image spatiotemporal fusion
International Journal of Remote Sensing, 2023Convolutional Neural Networks (CNN) are useful models for spatiotemporal fusion, especially under strong temporal changes. Convolutional layers with receptive fields of various sizes produce hierarchical features that can improve prediction performance ...
F. Erdem, U. Avdan
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Spatiotemporal Reflectance Fusion via Tensor Sparse Representation
IEEE Transactions on Geoscience and Remote Sensing, 2022Tradeoffs between the spatial and temporal resolutions of current satellite instruments limit our ability to conduct high-quality and continuous monitoring of the earth's surface dynamics. Spatiotemporal image fusion has become increasingly necessary to obtain remote sensing images with high spatiotemporal resolution.
Yidong Peng +6 more
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Touch Gesture Recognition Using Spatiotemporal Fusion Features
IEEE Sensors Journal, 2022The touch gesture is one of the most essential and effective means to transfer affective feelings and intents in humans’ communication. For an intelligent agent or a robot, the ability to automatically detect and recognize human touch can realize efficient and natural human–robot interaction.
Yun-Kai Li +2 more
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Spatiotemporal Reflectance Fusion Using a Generative Adversarial Network
IEEE Transactions on Geoscience and Remote Sensing, 2022The spatiotemporal reflectance fusion method is used to blend high-temporal and low-spatial resolution images with their low-temporal and high-spatial resolution counterparts that were previously acquired by various satellite sensors. Recently, a wide variety of learning-based solutions have been developed, but challenges remain.
Cheng Shang +7 more
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Spatiotemporal-Spectral Fusion for Gaofen-1 Satellite Images
IEEE Geoscience and Remote Sensing Letters, 2022Due to the limitations of hardware technology, satellite sensors cannot obtain images with high temporal, spatial, and spectral resolutions at the same time. Current spatiotemporal fusion methods try to solve the contradiction between temporal resolution and spatial resolution, which cannot achieve good reconstruction accuracy partly because the data ...
Jingbo Wei +3 more
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Spatiotemporal Reflectance Fusion via Sparse Representation
IEEE Transactions on Geoscience and Remote Sensing, 2012This paper presents a novel model for blending remote sensing data of high spatial resolution (HSR), taken at infrequent intervals, with those available frequently but at low spatial resolution (LSR) in the context of monitoring and predicting changes in land usage and phenology.
Bo Huang, Huihui Song
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An Intelligent Multiscale Spatiotemporal Fusion Network Model for TCM
IEEE Sensors Journal, 2023In the process of milling, accurate and reliable monitoring of tool condition monitoring (TCM) is essential to ensure machining quality and efficiency.
Y. Quan +3 more
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