A client device configured with a neural network includes a processor, a memory, a user interface, a communications interface, a power supply and an input device, wherein the memory includes a trained neural network received from a server system that has trained and configured the neural network for the client device. A server system and a method of training a neural network are disclosed.

Techniques are disclosed for generating a sequence of symbols based on input data for a neuro-linguistic model. The model may be used by a behavior recognition system to analyze the input data. A mapper component of a neuro-linguistic module in the behavior recognition system receives one or more normalized vectors generated from the input data. The mapper component generates one or more clusters based on a statistical distribution of the normalized vectors. The mapper component evaluates statistics and identifies statistically relevant clusters. The mapper component assigns a distinct symbol to each of the identified clusters.

A method for recognizing a text, an electronic device and a storage medium. An implementation of the method comprises: obtaining a multi-dimensional first feature map of a to-be-recognized image; performing, based on feature values in the first feature map, feature enhancement processing on each feature value in the first feature map; and performing a text recognition on the to-be-recognized image based on the first feature map after the enhancement processing.

A method for training a text positioning model includes: obtaining a sample image, where the sample image contains a sample text to be positioned and a text marking box for the sample text; inputting the sample image into a text positioning model to be trained to position the sample text, and outputting a prediction text box for the sample image; obtaining a sample prior anchor box corresponding to the sample image; and adjusting model parameters of the text positioning model based on the sample prior anchor box, the text marking box and the prediction text box, and continuing training the adjusted text positioning model based on a next sample image until model training is completed, to generate a target text positioning model.

The present disclosure provides techniques for encoding and decoding characters for optical character recognition. The techniques involve determining sets of numbers for encoding a character set where each number in a particular set of numbers for encoding a particular character is mapped to a graphical unit (e.g., radical) of the particular character. A mapping between each set of numbers in the possible encodings and the character set may be determined based the closest character already encoded. A machine learning model may be trained to perform optical character recognition using training data labeled using the set of encodings and the mappings.

An image processing method implemented by a computer includes extracting feature points from captured images that are sequentially generated by an image capture device and include at least a first captured image and a second captured image generated prior to the first captured image, determining whether the number of feature points extracted from the first captured image exceeds a threshold value, and specifying a location of the first captured image relative to the second captured image upon determining that the number of the feature points extracted from the first captured image is below the threshold value.

An apparatus for document recognition according to an embodiment includes a document type analyzer that analyzes a type of a recognition target document based on document feature vector extracted from one or more partial images obtained by color space conversion of one or more partial regions of the recognition target document, and an information extractor that extracts value information from one or more information search images organized in a grid form based on a position of key information of the recognition target document.

This invention relates generally to machine vision systems, and more particularly, to the detection of anomalies in scenes observed by imaging sensors.

There are provided a font creation apparatus, a font creation method, and a font creation program capable of generating, from small-number character images having a desired-to-be-imitated style, a complete font set for any language having the same style as the character images. A feature amount extraction unit (40) receives a character image (32) of a first font having a desired-to-be-imitated style and extracts a first feature amount of the first font of the character image (32). An estimation unit (42) estimates a transformation parameter between the extracted first feature amount and a second feature amount of a reference second font (34). A feature amount generation unit (44) generates a fourth feature amount of a second font set to be created by transforming a third feature amount of a complete reference font set (36) based on the estimated transformation parameter. A font generation unit (46) generates a complete second font set by converting the generated fourth feature amount of the second font set into an image.

The present invention provides an automatic container loading and unloading apparatus and method. The apparatus comprises: a data acquisition module, used for scanning a container truck panel to obtain laser point cloud data; a data preprocessing module, used for segmenting a laser point cloud on a surface of the container truck panel from the laser point cloud data; a key point extraction module, used for performing edge extraction on the laser point cloud on the surface of the container truck panel to obtain discrete points on edges of the keel of the container truck panel; and a straight line fitting module, used for performing random sample consensus straight line fitting on the discrete points on the edges of the keel of the container truck panel to obtain spatial straight lines of the edges of the keel of the truck panel. The automatic container loading and unloading apparatus and method provided by the present invention using spatial straight lines on the edges of the keel of the container truck panel for computing processing, thereby achieving stronger robustness and higher accuracy, so that a container is loaded onto the container truck panel with higher precision and lower calculation amount.