5 results about "Base function" patented technology

The application discloses a morphing text detection method and device and a storage medium. The method comprises the following steps: extracting image features of a to-be-processed image, the to-be-processed image being an image collected from a specified text carrier, and the specified text carrier being easy to deform under stress; inputting the image features into a control point detection network to obtain an edge control point sequence; inputting the edge control point sequence into a differentiable B-spline layer to perform matrix multiplication calculation on a base function matrix and the edge control point sequence, thereby obtaining a B-spline curve point sequence, and the base function matrix being a two-dimensional matrix composed of B-spline base function values; and generating a text detection frame based on the B-spline curve point sequence. The operation of the differentiable B-spline layer is differentiable in a deep learning framework, and the gradient can be back propagated to the parameters of the control point detection network through the differentiable B-spline layer, thereby realizing integrated end-to-end optimization of text detection and curve fitting and significantly improving the performance of the model in a complex morphing text detection task.

The present disclosure relates to a computer-implemented method for representing a data set including at least one n-dimensional data element representing visual information, the method comprising obtaining (210) the data set, obtaining (220) a dictionary set including a plurality of dictionaries, each dictionary including at least one basis function (102), assigning (230) each at least one data element to a dictionary, wherein the set of basis functions represents an m-dimensional transform domain, transforming (240) at least one data element to the transform domain using a corresponding dictionary of basis functions, wherein each data element is defined by an associated set of coefficients, sparsely (250) the set of coefficients, and forming (260) a representation of the visual information including the coefficient data set and the corresponding dictionary.

Embodiments relate to a system for generating a language output. The system can include a function call system including a processor with an interfacing module configured to interface the processor with a database and a natural language processing (NLP) model. The processor can generate a function call by: importing a base function class for identifying function calling programming code within the NLP model; defining a function for the function call; defining an output format for a response of the function call. The system can include an interfacing system configured to: generate a user interface configured to receive a human generated input; generate a prompt including the function call; and transmit the function call to the NLP model to generate a response that is a recognition of text, a generation text, and / or prediction of text based on a human generated input.

Embodiments relate to a system for generating a language output. The system can include a function call system including a processor with an interfacing module configured to interface the processor with a database and a natural language processing (NLP) model. The processor can generate a function call by: importing a base function class for identifying function calling programming code within the NLP model; defining a function for the function call; defining an output format for a response of the function call. The system can include an interfacing system configured to: generate a user interface configured to receive a human generated input; generate a prompt including the function call; and transmit the function call to the NLP model to generate a response that is a recognition of text, a generation text, and / or prediction of text based on a human generated input.

The application discloses a generation method of a model training tool, a model training method and device, and belongs to the technical field of computers. The method comprises the following steps: acquiring a first function from a first function library, and acquiring a second function with the same function as the first function from a second function library, wherein the first function is a function running on a CPU, and the second function is a function running on a GPU; acquiring first parameter information of the first function and second parameter information of the second function; generating a parameter set according to the first parameter information and the second parameter information; adjusting the first function and / or the second function according to the parameter set; generating a base function according to the adjusted first function and the adjusted second function; and obtaining a base function library tool according to the base function.