A display control integrated circuit (IC) applicable to performing real-time video content text detection and speech automatic generation in a display device may include a pre-processing circuit, a character recognition circuit and a post-processing circuit. The pre-processing circuit may input a video signal to obtain a real-time video content carried by the video signal, and perform preliminary text detection on the real-time video content to generate a series of segmented character images to indicate a subtitle. The character recognition circuit may perform character recognition on the series of segmented character images to generate a series of characters, respectively. The post-processing circuit may perform vocabulary correction on the series of characters to selectively replace any erroneous character with a correct character to generate one or more vocabularies, for performing speech automatic generation.

A character recognition method includes the following operations: determining that the image of character to be identified corresponds to a matching character of several registered characters according to several vector distances to be identified between a vector of an image of character to be identified and several vectors of several registered character images of several registered characters, and storing a matching vector distance between the vector of the image of character to be identified and a vector of the matching character by a processor; and storing a data of the matching character according to the image of character to be identified when the matching vector distance is less than a vector distance threshold by the processor.

According to one embodiment, a reading system includes an extractor, a determiner, and a reader. The extractor extracts a candidate image from an input image. The candidate image is a candidate of a portion of the input image in which a segment display is imaged. The determiner uses the candidate image and a mask to calculate a match ratio indicating a certainty of a segment display being included in the candidate image, and determines that the candidate image is an image of a segment display when the match ratio is not less than a threshold. The mask and the threshold are preset. The reader reads a numerical value displayed in a segment display from the candidate image determined to be an image of a segment display.

A method and apparatus for adaptively displaying a handwriting input on an electronic device are provided. The method includes receiving a handwriting input from an electronic device, detecting handwriting features in the handwriting input and comparing the handwriting features with stored handwriting feature data, determining, according to a result of the comparing, whether a subject of the handwriting input is an existing user or a new user, and displaying, according to the determination, a subsequent handwriting input by the subject of the handwriting input to match a target handwriting input style.

An image object recognition method, apparatus, and computer device are provided. The image object recognition method includes: performing feature extraction in the direction of a horizontal angle of view and in the direction of a vertical angle of view of an image respectively, to extract a lateral feature sequence and a longitudinal feature sequence of the image; fusing the lateral feature sequence and the longitudinal feature sequence to obtain a fused feature; activating the fused feature by using a preset activation function to obtain an image feature; and recognizing an object in the image by decoding the image feature. This solution can improve the efficiency of the object recognition.

Systems and methods for detecting and aligning land property boundaries on aerial imagery are provided. The system receives an aerial imagery having land properties. The system applies a feature encoder having a plurality of levels to the aerial imagery. A first level of the plurality of levels includes a convolution block and a discrete wavelet transform layer. The discrete wavelet transform layer decomposes an input feature tensor to the first level into a low-frequency band and a high-frequency band. The high-frequency band is cached and processed with side-convolutional blocks before the high-frequency band are passed to a feature decoder. The system applies the feature decoder to an output of the feature encoder based at least in part on one of inverse discrete wavelet transform layers. The system determines boundaries of the one or more land properties based at least in part on a boundary cross-entropy loss function.

Output can be provided from a selected biometric analysis task that is one of a plurality of biometric analysis tasks based on an image provided from an image sensor. The selected biometric analysis task can be performed in a deep neural network that includes a common feature extraction neural network, a plurality of biometric task-specific neural networks and a plurality of expert pooling neural networks that perform the plurality of biometric analysis tasks by inputting the image to the common feature extraction network to determine latent variables. The latent variables can be input to the plurality of biometric task-specific neural networks to determine a plurality of first outputs. Concatenated first output results can be formed and the concatenated plurality of first result outputs and the latent variables can be input to the plurality of expert pooling neural networks to determine one or more biometric analysis task outputs.

A number plate information specifying device includes an image acquisition unit that acquires a number plate image, a feature point extraction unit that extracts a feature point from the number plate image, a degree of similarity calculation unit that references a learning data set in which a plurality of feature points are recorded in association with a plurality of pieces of number plate information and calculates degrees of similarity for the feature points recorded in the learning data set that correspond to the feature point extracted from the number plate image, a vote value calculation unit that, on the basis of the degrees of similarity, calculates vote values for the pieces of number plate information recorded in the learning data set, and a specifying unit that specifies the piece of number plate information that has the highest vote value as the number plate information displayed in the number plate image.

A hotspot accessory camera connectable to a hotspot via a physical connection is provided. The hotspot accessory camera may include edge processing and/or artificial intelligence capabilities for image/video processing of images/video captured by the hotspot accessory camera. The hotspot accessory camera may include a base that accepts a hotspot device, and at least one actuatable arm adapted to hold one or more cameras to effectuate image/video capture.

A display apparatus includes circuitry to receive an input of hand drafted input data displayed as an object on a display. The circuitry converts the hand drafted input data into one of a text and a shape and determines whether the one of the text and the shape corresponds to a corresponding one of a recognition character string and a recognition shape set in advance. In a case that the one of the text and the shape corresponds to the corresponding one of the recognition character string and the recognition shape, the circuitry displays a display component based on the corresponding one of the recognition character string and the recognition shape. The display component is for receiving a user operation for generating an electronic signature in relation to the object. The circuitry generates the electronic signature in response to receiving selection of the display component.