TY - JOUR
AU1 - Liu, Min
AB - When analyzing the environmental development of coastal areas, the main basis used by researchers for analysis is the data information collected by remote sensing sensors. In the process of research and analysis, experts divided the areas displayed by remote sensing images into three types based on the characteristics of ocean areas, land, and intermediate zones, namely, sea areas, coastal beaches, and land areas. Today, with the continuous development of science and technology, people can choose the most appropriate image research method according to the development characteristics of different regions to better study the spatial distribution and geographic distribution of images. In the current era of development, the level of development of robot services is constantly improving. In order to improve the intelligence of robot service functions, people have begun to study the ability of machines to recognize human activities, and strive to meet the needs of development in all aspects. This article analyzes the characteristics of robot visual action recognition, compares and analyzes three different action representation methods, and uses deep learning related technologies to improve the level of action recognition.
TI - Image recognition of coastal environment and aerobics sports based on remote sensing images based on deep learning
JF - Arabian Journal of Geosciences
DO - 10.1007/s12517-021-08169-x
DA - 2021-09-01
UR - https://www.deepdyve.com/lp/springer-journals/image-recognition-of-coastal-environment-and-aerobics-sports-based-on-fagzOdBSeA
VL - 14
IS - 18
DP - DeepDyve
ER -