Spatiotemporal distribution and dynamics evolution of artificial intelligence development in China.

The quantified measurement and comprehensive analysis of artificial intelligence development (AIDEV) are vital for countries to form AI industrial ecology and promote the long-term development of regional AI technology. Based on the innovation ecosystems (IE) theory, this paper constructs an evaluation system to measure and analyze the spatiotemporal distribution and dynamic evolution of the AIDEV in China from 2011 to 2020. The results show that the AIDEV of China presents an overall upward trend and an obvious unbalance in the spatial distribution which is "eastern > central > western".

A hybrid generative adversarial network for weakly-supervised cloud detection in multispectral images.

Cloud detection is a crucial step in the optical satellite image processing pipeline for Earth observation. Clouds in optical remote sensing images seriously affect the visibility of the background and greatly reduce the usability of images for land applications. Traditional methods based on thresholding, multi-temporal or multi-spectral information are often specific to a particular satellite sensor.

Unsupervised Simplification of Image Hierarchies via Evolution Analysis in Scale-Sets Framework.

Region-based hierarchical image representation is crucial in many computer vision applications. However, in practice, an image hierarchy is usually dense, and contains many less informative branches. It is expected that a hierarchy should be accurate and simplified, which is not only desirable for different applications, but also saves considerable computational load for the further analysis.

An edge embedded marker-based watershed algorithm for high spatial resolution remote sensing image segmentation.

This correspondence proposes an edge embedded marker-based watershed algorithm for high spatial resolution remote sensing image segmentation. Two improvement techniques are proposed for the two key steps of maker extraction and pixel labeling, respectively, to make it more effective and efficient for high spatial resolution image segmentation. Moreover, the edge information, detected by the edge detector embedded with confidence, is used to direct the two key steps for detecting objects with weak boundary and improving the positional accuracy of the objects boundary.