7 results about "Sample distance" patented technology

The application discloses a boundary sample data enhancement method and device for knowledge distillation and a computer storage medium. The method comprises the following steps: before knowledge distillation is performed, the output of a teacher model is used to modify samples in each original data set along the decision boundary of the teacher model step by step, and a plurality of boundary samples suitable for knowledge distillation are expanded. In each iteration, the original sample or each sample modified in the last iteration is used as a basic sample, the approximate tangent plane of the decision boundary near the sample is calculated by using the output of the teacher model, and the sample is modified along multiple directions on the tangent plane; then, the modified sample is modified to be located near the boundary; finally, a plurality of samples farthest from other basic samples are selected as the result of the modification in the round and the basic samples for the next iteration. The application can meet the demand for data enhancement in current image classifier knowledge distillation.

The application discloses a semantic segmentation model training method, a semantic segmentation method, a device and equipment, relates to the technical field of artificial intelligence, and particularly relates to the technical field of deep learning, semantic segmentation, automatic driving and the like. The method comprises the following steps: determining sample point cloud data corresponding to a sample object from original point cloud data based on a preset down-sampling screening mode; the sample object comprises a compulsory object and a to-be-screened object; performing dimension reduction mapping on sample points in the sample point cloud data based on a preset projection rule to obtain sample distance images corresponding to the sample points; and training a semantic segmentation model according to sample label data corresponding to the sample distance images and the sample point cloud data. Through the above technical scheme, the accuracy of semantic segmentation can be improved.

A method of coding implemented by a decoding device or encoding device, the method comprising obtaining a value of an angle parameter for a current block; obtaining a value of a width of the current block and a value of a height of the current block; calculating a ratio value between the value of the width and the value of height; obtaining a first value according to the value of angle parameter and the ratio value; calculating a sample distance value for a sample in the current block according to the first value; obtaining a prediction value for the sample in the current block according to the sample distance value.

The SVD algorithm separates a clutter subspace, a target subspace and a noise subspace in radar echoes through singular value decomposition, and the purpose of clutter suppression is achieved. However, due to aliasing of the target and the sea clutter, the clutter suppression effect can be affected by clutter subspace division. In order to solve the problem that the clutter subspace is difficult to determine after the radar echo signal is subjected to SVD decomposition, the invention provides a method for adaptively selecting the clutter subspace by using an improved K-means clustering method. Aiming at the problems that K-means is sensitive to the initial centroid and different characteristic parameters are different in the aspects of statistical stability and anti-noise performance, the initial centroid is fixed, and the sample distance is calculated in a weighted mode. According to the method, after four characteristics of singular value distribution, echo component correlation, Doppler bandwidth and relative Doppler variable coefficient are used as K-means input, clutter subspaces are selected in a self-adaptive mode, and the purpose of clutter suppression is achieved by mapping signals into orthogonal spaces of the clutter subspaces.

The invention discloses an extreme weather prediction method and system, and relates to the technical field of artificial intelligence. The method comprises the following steps: collecting multi-modal meteorological observation data; performing space-time alignment and quality correction to obtain an assimilation data set; adjusting a feature extraction weight based on a quality identifier, and projecting the assimilation data set to a low-dimensional hidden space to obtain a hidden space feature vector; based on the sample distance measurement of the hidden space, adopting a meta-learning framework to carry out multi-task prediction on the feature vector of the hidden space; performing multi-target collaborative optimization and antagonism training on the neural network by using the prediction result to obtain a prediction model; and verifying the prediction result by using a digital twin simulation environment to obtain a verification result, and updating model parameters of the prediction model. According to the method, the problem of insufficient prediction precision caused by a complex coupling relationship of meteorological factors and data isomerism is effectively solved, and the accuracy and reliability of extreme weather evolution trend prediction are improved.

The present application relates to a kind of high-throughput testing device and method of electrical properties of component gradient film material, belong to material performance test field, solve the problem that the measurement result is wrong caused by the easy damage of scanning probe to sample.It includes: probe device, located above the sample to be measured, including probe and its fixing device, for detecting the response of sample to external field;Electrical property testing device, for applying external field to sample, collecting the response signal detected by probe, and transmitting the collected data to computer;Displacement device, for loading sample and adjusting the position of sample;Probe-sample distance monitoring device, for real-time monitoring the distance between probe and sample and feeding back to computer;Computer, for controlling displacement device to stop moving at the moment when probe and sample contact, and calculating the electrical properties of sample based on the collected data.The testing device of electrical properties of component gradient film is realized, which can effectively avoid sample damage, fast, efficient and accurate.