Abstract: The present invention discloses a CEEMDAN-based method for screening and monitoring soil moisture stress in farmland, characterised by the steps: preprocessing of remote sensing images, construction of NDVI long time series, CEEMDAN decomposition, calculation of statistical descriptors, screening of soil moisture stress sequences, ground data measurement, construction of soil moisture stress characteristic curves, fitting of soil moisture stress response characteristic curves and predicting the content of soil moisture stress. The invention adopts CEEMDAN decomposition, which solves the problems of noise residue and low reconstruction accuracy in the previous methods, and the high reconstruction accuracy of decomposed component data is more conducive to capturing the transient effects of soil moisture stress, and realizes the screening and extraction of soil moisture stress by combining with the ground measured data.

Abstract: A method of calculating a size of a Gaussian kernel in a crowd counting system. The method includes dividing a crowd density map into several areas at equal intervals; calculating an estimated value of average distance of k nearest heads with respect to a head center point coordinate of a current person; calculating a weight coefficient for an average distance of k nearest heads; calculating a size of a Gaussian kernel corresponding to the head center point coordinate of the current person; determining whether there are any head center point coordinates of which sizes of Gaussian kernels have not been calculated yet in training data. If there are head center point coordinates of which sizes of the Gaussian kernels have not been calculated in the training data, recalculating an estimated value of average distance of k nearest heads with respect to another head center point coordinate of another current person.

Abstract: The present disclosure relates to hinged engineering machinery, a panoramic surround-view system and a calibration method thereof. The hinged engineering machinery comprises at least two hinged structure segments sequentially connected by means of a hinged frame, wherein the at least two hinged structure segments comprise a first hinged structure segment, the first hinged structure segment comprising a first vehicle body and a cab arranged on the first vehicle body.

Abstract: Implementations provide an improved system for presenting search results based on entity associations of the search items. An example method includes generating first-level clusters of items responsive to a query, each cluster representing an entity in a knowledge base and including items mapped to the entity, merging the first-level clusters based on entity ontology relationships, applying hierarchical clustering to the merged clusters, producing final clusters, and initiating display of the items according to the final clusters. Another example method includes generating first-level clusters from items responsive to a query, each cluster representing an entity in a knowledge base and including items mapped to the entity, producing final clusters by merging the first-level clusters based on an entity ontology and an embedding space that is generated from an embedding model that uses the mapping, and initiating display of the items responsive to the query according to the final clusters.

Abstract: Implementations provide an improved system for presenting search results based on entity associations of the search items. An example method includes generating first-level clusters of items responsive to a query, each cluster representing an entity in a knowledge base and including items mapped to the entity, merging the first-level clusters based on entity ontology relationships, applying hierarchical clustering to the merged clusters, producing final clusters, and initiating display of the items according to the final clusters. Another example method includes generating first-level clusters from items responsive to a query, each cluster representing an entity in a knowledge base and including items mapped to the entity, producing final clusters by merging the first-level clusters based on an entity ontology and an embedding space that is generated from an embedding model that uses the mapping, and initiating display of the items responsive to the query according to the final clusters.