3results about How to "Realize the mapping" patented technology

This invention relates to the field of remote sensing water quality identification technology, and in particular to a method for identifying black and odorous water bodies based on a temporal convolutional network. By constructing a black and odorous water body identification model comprising a cascaded temporal convolutional network residual module, a channel attention module, a temporal attention module, a global average pooling layer, and a regressor module, and replacing the original output layer of the temporal convolutional network with the regressor module, a mapping from remote sensing image data to continuous water quality parameter predictions is achieved. This solves the technical problem of limited accuracy in identifying black and odorous water bodies by relying solely on general spectral features in existing technologies. Furthermore, by performing addition, subtraction, multiplication, and division operations on the original spectral bands to generate combined bands, and using the Pearson correlation coefficient method to select the original and combined bands with the highest correlation, a sample dataset is constructed by combining this with ground-based measured data. This further expands the sample size based on existing samples, significantly improving the model's learning efficiency.

The application relates to the technical field of marine ecological disaster monitoring, and discloses a green algae area estimation method based on an unmanned aerial vehicle non-orthographic operation mode, which comprises the following steps: firstly, spectrum energy analysis is used to determine a sea state mode and to inversely calculate a basic wave height, a vertical non-uniform atmospheric extinction model is constructed to perform physical defogging; secondly, a fluid-solid coupling damping coefficient is inversely calculated based on texture entropy and glare characteristics, and a green algae microscopic equivalent mean square slope is corrected; finally, pixel-level macroscopic slant range projection, a wave shielding compensation factor and a microscopic surface area correction factor are comprehensively used, and a Sigmoid smoothing truncation weight function is combined to calculate a green algae physical total surface area. The application solves the measurement error caused by the non-uniformity of atmospheric medium, wave shielding and the absence of microscopic geometric characteristics under non-orthographic observation, and significantly improves the monitoring accuracy under complex sea conditions.

This application provides a method and device for reading RFID tags. The method described in this application enables cellular networks to read RFID tags. During the reading process, it ensures compatibility between the cellular network and existing passive RFID tags, achieving a mapping between tag status and RRC status, thereby increasing the compatibility of the cellular network and improving the tag reading distance without modifying existing tag products. Furthermore, the method described in this application can be executed by a relay device, thus avoiding increased computational complexity and power consumption for the tags. It is compatible with passive RFID tags already deployed in business scenarios, ensuring smooth technological evolution.