8 results about "Combining character" patented technology

The present invention relates to a system that automatically generates 2D animations based on text and embeddings, maintaining visual and semantic consistency by combining model IDs and embeddings of characters, backgrounds, and motions. Information regarding scenes, characters, backgrounds, actions, and dialogue is extracted from input text content through natural language processing (NLP) and semantic analysis. By combining character embeddings and motion embeddings with model IDs, background images are synthesized to automatically generate animation scenes while maintaining consistency in the appearance and movement of the characters. Adaptive learning based on user feedback is performed to continuously improve the generation performance of the system, and post-production work is automated to maximize production efficiency. By enabling the efficient and consistent production of 2D animations in large-scale user environments, this system reduces production costs and time and supports non-experts in easily creating animations.

Systems and methods are disclosed herein for training a model to accurately determine whether two phrases are conversationally connected. A media guidance application may detect a first phrase and a second phrase, translate each phrase to a string of word types, append each string to the back of a prior string to create a combined string, determine a degree to which any of the individual strings matches any singleton template, and determine a degree to which the combined string matches any conversational template. Based on the degrees to which the individual and combination strings match the singleton and conversational templates, respectively, strengths of association are correspondingly updated.

The invention relates to a character recognition method and system, and the method comprises the steps: inputting a target image comprising a to-be-recognized statement into a trained character recognition model, and obtaining an initial recognition result; the to-be-recognized statement comprises a plurality of to-be-recognized characters; the initial recognition result comprises a result character with the highest result probability corresponding to each character to be recognized; inputting the plurality of result characters into a trained context word meaning scoring model to obtain a word meaning score of each result character; and obtaining a target result character of each to-be-recognized character according to the word meaning score and the result probability. According to the method, the target result character of the to-be-recognized character is obtained by combining character recognition and context semantic scoring, and character recognition of the statement is performed by integrating the character recognition dimension and the semantic analysis dimension, so that the accuracy of character recognition can be improved.

The application discloses a passenger car instrument information character matrix conversion method, comprising the following steps: firstly, using a pixel matrix group to deconstruct a defined instrument section to be described, and allocating a character to each matrix block according to a basic pixel block; then, performing unicode coding on the character to be expressed; then, performing space transformation processing on the character matrix of the space; finally, combining the calculated character block matrix and transmitting the combined character block matrix to an instrument medium to be displayed. The method has low requirements on the computing power of a chip, simplifies the instrument graphic display performance, and solves the instrument display problem of a low-cost chip.

The present invention provides a text recognition method, a text recognition network training method, and a device. The method comprises: inputting an image to be recognized into a text recognition network, obtaining character information and text region information output by the text recognition network, wherein the character information at least indicates the characters contained in the image and the positions of the characters; the text region information at least indicates the text region within the image where the text is located; determining the text region where the character is located based on the character positions and the text region information; and combining characters within the same text region according to the character positions to obtain the text content contained in the text region.

The present disclosure provides a traditional Chinese medical record named entity recognition method based on a multi-head attention mechanism, comprising the following steps: obtaining text data of a traditional Chinese medical record; combining character vectors and word vectors in the obtained text data and sending them into a Bi-GRU neural network for feature extraction to obtain global features; using a multi-head attention mechanism to provide potential semantic information for the character vectors and extract local features; inputting the global features and the local features into a conditional random field layer to obtain a named entity sequence labeling result of the text data; the present disclosure does not require a word segmentation operation, combines the features of characters and words to form a joint feature, controls the weights of the characters and the words using a hyperparameter, inputs the joint feature into an embedding layer, and adds spatial attention in the Bi-GRU layer to make up for the deficiency in extracting effective features, greatly improving the accuracy of entity recognition.

This character recognition device is provided with: a recognition unit that recognizes a character string from a captured image including a trailer captured by an imaging device; and a post-processing unit that performs a horizontal writing concatenation process to concatenate two character strings, among the character strings recognized by the recognition unit, that satisfy a horizontal writing concatenation condition for concatenating the two character strings of horizontal writing arranged in a horizontal direction in the captured image, and outputs the recognized character string including the concatenated character string.

To provide a character recognition method for easily reading a handwritten character string described over a plurality of lines on a ballot.SOLUTION: The character recognition method for reading handwritten characters written on a ballot via an information processor includes a step S4 of reading the handwritten characters written on the ballot via the information processor, a step S7 of identifying whether the number of lines of the read character strings read via the information processor is one or a plurality of lines, and a step S9 of recognizing the characters of the read character strings as they are when the number of lines of the read character strings is one. And a step S8 for combining the character strings of the respective continuous lines of the read character strings as one combined character strings and recognizing the characters of the combined character strings.SELECTED DRAWING: Figure 6