Abstract: A fracturing device, including a power unit, wherein the power unit comprises a muffling compartment, a turbine engine, an air intake unit, and a starter; the air intake unit is communicated with the turbine engine through an intake pipe, and configured to provide a combustion-supporting gas to the turbine engine; the air intake unit is located at the top of the muffling compartment, the muffling compartment comprises an accommodation space, the turbine engine and the starter are located in the accommodation space, and the starter is configured to start the turbine engine, the starter comprises a first electric motor.

Abstract: Some embodiments of the disclosure provide an air intake bypass recirculation structure with adjustable air entraining amount and controllable broadband noise which includes main body of the air intake bypass recirculation structure and an air entraining amount adjusting structure. In some examples, an air intake bypass recirculation cavity is formed in the main body of the air intake bypass recirculation structure. An air inlet of an air intake pipe and an air outlet of the air intake pipe are formed in two ends of the main body of the air intake bypass recirculation structure respectively. An airflow inlet of the air intake bypass recirculation structure and an airflow outlet of the air intake bypass recirculation structure are formed in the inner side of the main body of the air intake bypass recirculation structure. The air entraining amount adjusting structure is arranged in the air intake bypass recirculation cavity.

Abstract: The disclosure provides a method and a device for processing information, an electronic device, and a storage medium, belonging to a field of artificial intelligence including computer vision, deep learning, and natural language processing. In the method, the computing device recognizes multiple text items in the image. The computing device classifies multiple text items into a first set of name text items and a second set of content text items based on semantics of the text items. The computing device performs a matching operation between the first set and the second set based on a layout of the text items in the image, and determines matched name-content text items. The matched name-content text items include a name text item in the first set and a content text item matching the name text item and in the second set. The computing device outputs the matched name-content text items.

Abstract: A pre-training method for a Vision and Scene Text Aggregation model includes: acquiring a sample image-text pair; extracting a sample scene text from a sample image; inputting a sample text into a text encoding network to obtain a sample text feature; inputting the sample image and an initial sample aggregation feature into a visual encoding subnetwork and inputting the initial sample aggregation feature and the sample scene text into a scene encoding subnetwork to obtain a global image feature of the sample image and a learned sample aggregation feature; and pre-training the Vision and Scene Text Aggregation model according to the sample text feature, the global image feature of the sample image, and the learned sample aggregation feature.

Abstract: Disclosed herein is a particulate filter, in particular a catalyzed particulate filter, for use in an emission treatment system of an internal combustion engine. Provided are catalyzed particulate filters, emission treatment systems with catalyzed particulate filters, methods for manufacturing catalyzed particulate filters, and methods for controlling emissions in exhaust gas from internal combustion engines with catalyzed particulate filters.

Abstract: The presently claimed invention provides an emission control catalyst article comprising a substrate having an inlet axial end and an outlet axial end, a bottom washcoat layer coated on the 60 to 100% length of the substrate from the inlet axial end to the outlet axial end, and a top washcoat layer coated on the 60 to 100% length of the substrate from the inlet or the outlet or both end of the substrate such that the top coat covers at least 60% of the length of the bottom washcoat layer, wherein at least part of the top washcoat layer and/or the bottom washcoat layer comprises a first portion and a second portion, wherein the first portion begins at the inlet axial end or the outlet axial end of the substrate and exhibits a platinum group metal concentration of 2 to 100 times higher than the concentration of a platinum group metal in the second portion, wherein the first portion comprises 5-50% of the substrate volume and exhibits a three-dimensional axial and/or radial zone arrangement starting from the inl

Abstract: Disclosed herein is a catalytic article including a first layer having at least one first platinum group metal supported on a first support, where the first support includes an alumina and a first oxygen storage component, and the first oxygen storage component includes ceria-zirconia; a second layer including at least one second platinum group metal supported on a second support, where the second support includes an alumina and a second oxygen storage component, and the second oxygen storage component includes ceria-zirconia; and a substrate . Further disclosed herein is a process for preparing the catalytic article.

Abstract: The present invention provides a catalyst composition comprising a) platinum; b) rhodium; and c) a ceria-alumina composite, a zirconia composite or a mixture thereof, wherein platinum is supported on the ceria-alumina composite, zirconia composite or mixture thereof, wherein rhodium is supported on the ceria-alumina composite, zirconia composite or mixture thereof, wherein CeO2 in the ceria alumina composite is 1.0 to 50 wt. %, based on the total weight of the ceria-alumina composite, wherein the amount of ZrO2 in the zirconia composite is 50 to 99 wt. %, based on the total weight of the zirconia composite. The present invention also provides a catalytic article comprising the catalyst composition and its preparation.

Abstract: The present application discloses an image recognition method, apparatus, device, and a computer storage medium, which is related to a technical field of artificial intelligence, and in particular, to a technical field of image processing. The method includes: performing organ recognition on a human face image and marking positions of the human facial five sense organs in the human face image, obtaining a marked human face image; inputting the marked human face image into a backbone network model and performing feature extraction, obtaining defect features of the marked human face image outputted by different convolutional neural network levels of the backbone network model; and fusing the defect features of different levels that are located in a same area of the human face image, obtaining a defect recognition result of the human face image.

Abstract: An image recognition method is provided, which is related to a technical field of artificial intelligence, and in particular, to a technical field of image processing. An implementation includes: performing five-sense-organ recognition on a preprocessed human face image and marking positions of the human facial five sense organs in the human face image, to obtain the marked human face image; determining human face images at multiple scales of the marked human face image, inputting the human face images of multiple scales into a backbone network model, and performing feature extraction, to obtain a wrinkle feature of the human face image at each of the multiple scales; and fusing the wrinkle feature at each scale that is located in a same area of the human face image, to obtain a wrinkle recognition result of the human face image.

Abstract: A model determination method and electronic device is provided, and relates to the technical field of artificial intelligence and, in particular, to the field of computer visions and deep learning, and can be applied to image processing, image identification and other scenarios. A specific implementation solution includes an image sample and a text sample are acquired, wherein text data in the text sample is used for performing text description to target image data in the image sample; at least one image feature in the image sample is stored to a first queue, and at least text feature in the text sample is stored to a second queue; the first queue and the second queue are trained to obtain a first target model; and the first target model is determined as an initialization model for a second target model.

Abstract: The present disclosure generally relates to emission control catalyst articles comprising a platinum group metal (PGM) enriched zone, methods of making such emission control catalyst articles, and methods of using such emission control catalyst articles.

Abstract: Embodiments of the present disclosure provide a method and apparatus for training an image recognition model based on a semantic enhancement, a method and apparatus for recognizing an image, an electronic device, and a computer readable storage medium. The method for training an image recognition model based on a semantic enhancement comprises: extracting, from an inputted first image being unannotated and having no textual description, a first feature representation of the first image; calculating a first loss function based on the first feature representation; extracting, from an inputted second image being unannotated and having an original textual description, a second feature representation of the second image; calculating a second loss function based on the second feature representation, and training an image recognition model based on a fusion of the first loss function and the second loss function.

Abstract: A method and apparatus for identifying a display scene, a method and apparatus for training a model, a device, a storage medium and a computer program product are provided. An implementation of the method may comprise: acquiring a feature vector of a to-be-identified image and acquiring a base library feature vector set; ascertaining, from the base library feature vector set, at least two candidate feature vectors based on a similarity coefficient between the feature vector of the to-be-identified image and each feature vector in the base library feature vector set; performing threshold comparisons on similarity coefficients of the at least two candidate feature vectors, to obtain a target feature vector; and determining a display scene of the to-be-identified image based on a display scene tag corresponding to the target feature vector.

Abstract: A method, apparatus and system for retrieving an image is provided, the method comprises: detecting, in response to receiving a query request comprising a target image, a target subject from the target image; extracting a subject feature from the target subject if a confidence level of a detection box of the detected target subject is greater than a first threshold, the subject feature comprising an identical feature, a similar feature and a category; performing matching on the subject feature of the target image and a subject feature of a candidate image pre-stored in a database, to obtain a similarity score and an identicalness score of the candidate image; and selecting, according to the similarity score and the identicalness score, a predetermined number of candidate images as a search result for output.

Abstract: The present disclosure provides binder compositions formed with a plurality of binder materials having differing mean particles, the binder compositions being useful to improve washcoat adhesion on a substrate. Adhesion can be improved related to an increase in the binder concentration without a significant or substantial increase in associated viscosity. Such binder compositions can comprise a first binder material formed of a plurality of particles having a first mean particle size and a second binder material formed of a plurality of particles having a second mean particle size, wherein a ratio of the first mean particle size to the second mean particle size about 2 or greater. The present disclosure further provides catalyst compositions, catalyst articles, and emission systems incorporating the binder compositions.

Abstract: The present disclosure proposes an end-to-end text recognition method and apparatus, computer device and readable medium. The method comprises: obtaining a to-be-recognized picture containing a text region; recognizing a position of the text region in the to-be-recognized picture and text content included in the text region with a pre-trained end-to-end text recognition model; the end-to-end text recognition model comprising a region of interest perspective transformation processing module for performing perspective transformation processing for the text region. The technical solution of the present disclosure does not need to serially arrange a plurality of steps, and may avoid introducing the accumulated errors and may effectively improve the accuracy of the text recognition.

Abstract: The disclosure provides a method and a device for processing information, an electronic device, and a storage medium, belonging to a field of artificial intelligence including computer vision, deep learning, and natural language processing. In the method, the computing device recognizes multiple text items in the image. The computing device classifies multiple text items into a first set of name text items and a second set of content text items based on semantics of the text items. The computing device performs a matching operation between the first set and the second set based on a layout of the text items in the image, and determines matched name-content text items. The matched name-content text items include a name text item in the first set and a content text item matching the name text item and in the second set. The computing device outputs the matched name-content text items.

Abstract: The disclosure provides a method for recognizing a license plate. The implementation includes: obtaining a feature map including a plurality of feature vectors of a license plate region; sequentially inputting the plurality of feature vectors based on a first order into a first recurrent neural network for encoding to obtain a first code of each of the plurality of feature vectors; sequentially inputting the plurality of feature vectors based on a second order into a second recurrent neural network for encoding to obtain a second code of each of the plurality of feature vectors; generating a plurality of target codes of the plurality of feature vectors based on the first code of each of the plurality of feature vectors and the second code of each of the plurality of feature vectors; and decoding the plurality of target codes to obtain a plurality of characters in the license plate.

Abstract: An image recognition method is provided, which is related to a technical field of artificial intelligence, and in particular, to a technical field of image processing.