Abstract: Provided are an AR translation processing method and an electronic device, which relate to the technical field of communications. By the method, in a scenario in which an electronic device is used for AR translation, a pose change of the electronic device can be detected in real time, and feature matching can be performed on a plurality of consecutive frames of images acquired by a camera, so that whether to-be-translated text needs to be fully translated or partially translated, or needs not to be translated can be determined based on the pose change of the electronic device and a feature matching result, and therefore a corresponding translation trigger strategy is selected. In this way, repeated translation can be effectively avoided, thereby saving computing resources in the AR translation process and improving the translation efficiency to a particular extent.

Abstract: Provided are a display substrate, a preparation method thereof and a display apparatus. The display substrate includes a first semi-conductive layer, a first conductive layer, a second conductive layer, a second semi-conductive layer, a third conductive layer, an interlayer insulating layer and an organic layer stacked on a substrate. The first semi-conductive layer includes an active layer of a polysilicon transistor, the first conductive layer includes a gate electrode of a polysilicon transistor and a first electrode plate of a storage capacitor, the second conductive layer includes a second electrode plate of a storage capacitor, the second semi-conductive layer includes an active layer of an oxide transistor, and the third conductive layer includes a gate electrode of an oxide transistor.

Abstract: An exemplary two-step method for power system inertia online estimation is described. The first step is to accurately estimate the POI-level aggregated inertia. The second step is to calculate the system-level inertia constant by weighting all the POI-level aggregated inertia and to monitor the inertia spatial distribution. In one example embodiment, the PMU is installed at POI, the frequency spatial difference is considered, and the mechanical power is carefully treated.

Abstract: The present disclosure provides an image recognition method and apparatus, a device and a non-volatile computer storage medium. In embodiments of the present disclosure, it is feasible to obtain the to-be-recognized image of a designated size, extract the different-area image from the to-be-recognized image, and obtain the image feature of the different-area image according to the different-area image, so as to obtain the recognition result of the to-be-recognized image, according to the image feature of the different-area image and a preset template feature. In this way, recognition processing can be performed for images in a limited number of classes without employing the deep learning method based on hundreds of thousands of even millions of training samples.

Abstract: Embodiments of the present disclosure provide a method and device for labelling a point of interest, a computer device, and a storage medium. The method includes the following. Image data to be labelled is obtained. The image data includes an image to be labelled and a collection location of the image to be labelled. Feature extraction is performed on the image to be labelled to obtain a first image feature of the image to be labelled. A first reference image corresponding to the image to be labelled is determined based on a similarity between the first image feature and a second image feature corresponding to each reference image in an image library. The point of interest of the image to be labelled is labelled based on a category of the first reference image and the collection location of the image to be labelled.

Abstract: A coin identification method and device, as well as a coin register are provided, which are related to a field of image identification. A specific implementation includes: extracting, from a to-be-identified image including coins, image blocks corresponding to the coins, to form an input coin set; inputting the input coin set into a coin classification model, to obtain categories and a classification confidences of the image blocks of the coins in the input coin set, wherein the category includes a face value of the coin; incorporating an image block, with a classification confidence reaching a threshold, of a coin of the input coin set into a first coin set; and determining a face value indicated by a category of the image block of the coin in the first coin set as a final face value of the coin in the first coin set.

Abstract: The present disclosure relates to a method and a device for training an image recognition model and a related device. The method includes: extracting sub-image feature data from a detection frame sub-image of an input image; determining element feature data matching the sub-image feature data from an index element database; and outputting images related to the element feature data as training images for training the image recognition model. The index element database is built in advance based on a plurality of element feature data extracted from a plurality of candidate images.

Abstract: Embodiments of the present disclosure provide a method and apparatus for processing an image. The method may include: acquiring a feature of a target image; acquiring a style of the target image, and searching a feature most similar to the feature of the target image from a set of image related information of the style, where the set of image related information comprises features of multiple groups of paired images; and using a paired image of an image corresponding to the found feature as a paired image of the target image and outputting the paired image of the target image.

Abstract: A coin identification method and device, as well as a coin register are provided, which are related to a field of image identification. A specific implementation includes: extracting, from a to-be-identified image comprising coins, image blocks corresponding to the coins, to form an input coin set; inputting the input coin set into a coin classification model, to obtain categories and a classification confidences of the image blocks of the coins in the input coin set, wherein the category comprises a face value of the coin; incorporating an image block, with a classification confidence reaching a threshold, of a coin of the input coin set into a first coin set; and determining a face value indicated by a category of the image block of the coin in the first coin set as a final face value of the coin in the first coin set.

Abstract: Embodiments of the present disclosure provide a method and device for labelling a point of interest, a computer device, and a storage medium. The method includes the following. Image data to be labelled is obtained. The image data includes an image to be labelled and a collection location of the image to be labelled. Feature extraction is performed on the image to be labelled to obtain a first image feature of the image to be labelled. A first reference image corresponding to the image to be labelled is determined based on a similarity between the first image feature and a second image feature corresponding to each reference image in an image library. The point of interest of the image to be labelled is labelled based on a category of the first reference image and the collection location of the image to be labelled.

Abstract: Embodiments of the present disclosure provide a method and apparatus for processing an image. The method may include: acquiring a feature of a target image; acquiring a style of the target image, and searching a feature most similar to the feature of the target image from a set of image related information of the style, where the set of image related information comprises features of multiple groups of paired images; and using a paired image of an image corresponding to the found feature as a paired image of the target image and outputting the paired image of the target image.

Abstract: The present disclosure relates to a method and a device for training an image recognition model and a related device. The method includes: extracting sub-image feature data from a detection frame sub-image of an input image; determining element feature data matching the sub-image feature data from an index element database; and outputting images related to the element feature data as training images for training the image recognition model. The index element database is built in advance based on a plurality of element feature data extracted from a plurality of candidate images.

Abstract: The present disclosure provides a watermark image processing method and apparatus, a device and a computer readable storage medium. In the embodiments of the present disclosure, it is feasible to obtain at least one similar image approximate to the watermark image according to the watermark image including the watermark, and obtain a replaceable image of each similar image of said at least one similar image in the watermark area, according to a watermark area where the watermark is located in the watermark image so that it is possible to obtain a carrier image not including the watermark, according to the watermark image and the replaceable image of said each similar image in the watermark area. Since the replaceable image of the similar image in the watermark area is employed to obtain the carrier image not including the watermark, the valid content in the watermark image covered by the watermark is restored and thereby the reliability of the image is improved.

Abstract: A method for recognizing a picture, a method and an apparatus for labelling a picture, and a storage medium. The method for recognizing a picture comprises: acquiring a clothes picture labelled with a positioning key point and a clothes wearing region (S310); extracting, based on the locations of the clothes wearing region and the positioning key point, at least one picture region representing a feature region from the clothes picture (S320); and respectively acquiring feature information representing the feature region based on a region feature recognition model corresponding to the feature region (S330). By labelling the positioning key point, a picture representing a clothes content in the clothes picture is positioned, so that the interference of a background content in the clothes picture is reduced.

Abstract: The present application discloses an image-based information acquisition method and apparatus. The information acquisition method comprises: acquiring a first image; determining a second image matching the first image from a preset image library; presenting first information related to a commercial item if the second image is associated with commercial item information; and presenting second information related to a video if the second image is associated with video information. The information acquisition method of the present application can directly use images as references for acquiring information, thereby implementing the objective of improving information acquisition efficiency and accuracy.

Abstract: The present disclosure provides a watermark image processing method and apparatus, a device and a computer readable storage medium. In the embodiments of the present disclosure, it is feasible to obtain at least one similar image approximate to the watermark image according to the watermark image including the watermark, and obtain a replaceable image of each similar image of said at least one similar image in the watermark area, according to a watermark area where the watermark is located in the watermark image so that it is possible to obtain a carrier image not including the watermark, according to the watermark image and the replaceable image of said each similar image in the watermark area. Since the replaceable image of the similar image in the watermark area is employed to obtain the carrier image not including the watermark, the valid content in the watermark image covered by the watermark is restored and thereby the reliability of the image is improved.

Abstract: The present disclosure provides a method and system for obtaining picture annotation data. The method comprises: obtaining a recognition result of a to-be-annotated picture; displaying the to-be-annotated picture and a corresponding recognition result on an annotation interface; using an annotator's selection of the recognition result in the annotation interface, to obtain annotation data of the to-be-annotated picture. According to the method and system for obtaining picture annotation data of the present disclosure, the annotator only needs to perform an operation of clicking the corresponding recognition result without manually inputting the name, and improves the annotation efficiency. The technical solution is particularly adapted for beforehand data preparation work of an image vertical type recognition algorithm, may substantially reduce costs of manually annotating pictures, and shorten the development cycle of picture recognition-type projects.

Abstract: The present disclosure provides an image recognition method and apparatus, a device and a non-volatile computer storage medium. In embodiments of the present disclosure, it is feasible to obtain the to-be-recognized image of a designated size, extract the different-area image from the to-be-recognized image, and obtain the image feature of the different-area image according to the different-area image, so as to obtain the recognition result of the to-be-recognized image, according to the image feature of the different-area image and a preset template feature. In this way, recognition processing can be performed for images in a limited number of classes without employing the deep learning method based on hundreds of thousands of even millions of training samples.

Abstract: A method for recognizing a picture, a method and an apparatus for labelling a picture, and a storage medium. The method for recognizing a picture comprises: acquiring a clothes picture labelled with a positioning key point and a clothes wearing region (S310); extracting, based on the locations of the clothes wearing region and the positioning key point, at least one picture region representing a feature region from the clothes picture (S320); and respectively acquiring feature information representing the feature region based on a region feature recognition model corresponding to the feature region (S330). By labelling the positioning key point, a picture representing a clothes content in the clothes picture is positioned, so that the interference of a background content in the clothes picture is reduced.

Abstract: The present application discloses an image-based information acquisition method and apparatus. The information acquisition method comprises: acquiring a first image; determining a second image matching the first image from a preset image library; presenting first information related to a commercial item if the second image is associated with commercial item information; and presenting second information related to a video if the second image is associated with video information. The information acquisition method of the present application can directly use images as references for acquiring information, thereby implementing the objective of improving information acquisition efficiency and accuracy.