Abstract: The present disclosure provides data processing methods and apparatuses, an electronic device and a storage medium. The method includes: obtaining a product sample set; obtaining combination features in specified dimensions of the product sample set by processing a second parameter based on a preset dimension reduction algorithm; obtaining influence scores respectively for the combination features in specified dimensions based on a first parameter and the combination features in specified dimensions; obtaining at least one combination feature ranked top by sorting the combination features based on the influence scores, and taking a raw parameter corresponding to the at least one combination feature as a cause of the product defect.

Abstract: Provided is a method for querying questions. The method includes: acquiring input information of a user; acquiring intention information of the user based on the input information of the user; determining an answer generation rule; and generating, based on the input information and the intention information, a first answer in accordance with the answer generation rule, and providing the first answer to the user.

Abstract: The present disclosure relates to an image data classification method, device and system, and relates to the field of computer technology. The method includes: inputting test image data into a neural network model trained by using an original training sample set for classification, and determining an image type to which the test image data belongs and a membership probability of the image data belonging to the image type; establishing an easy-to-classify data set, according to test image data with a membership probability greater than a first threshold; adding test image data in the easy-to-classify data set that has a classification accuracy rate less than or equal to a second threshold and a correct classification result to the original training sample set to generate an augmented training sample set; and using the augmented training sample set to train the neural network model so as to determine an image class.

Abstract: A data processing method includes: acquiring sample data of each sample of samples produced within a preset time period, the sample data including a value, which is acquired at each acquisition time, of a device parameter of a device through which the sample passes, and a test result of the sample; dividing sample data of the samples into data of positive samples and data of negative samples according to test results of the samples; determining a sample segment point of each sample according to values of the device parameter, so as to obtain N value groups of target values corresponding to each sample; and determining a related quantized value according to a difference between an M-th value group of a positive sample and an M-th value group of a negative sample.

Abstract: Provided is a method and device for detecting defect, a computer readable storage medium and an electronic device, the method including: acquiring (S310) a detection task, and acquiring various types of images corresponding to the detection task; acquiring (S320) defect detection models trained by a same initial model corresponding to the types of the images respectively; and obtaining (S330) defect detection results by performing defect detection on respective type of images using the defect detection model corresponding to the type of the images.

Abstract: A data processing method, includes: obtaining sample data in response to a user's input operation on a graphical interface, the sample data including characteristic data and detection data of samples; displaying a sample distribution diagram on the graphical interface based on the sample data; obtaining a focus threshold used for classifying positive and negative samples, the focus threshold being determined based on the detection data of the samples; displaying a mark of the focus threshold in the sample distribution diagram on the graphical interface; distinguishing data display effects of the positive and negative samples based on the focus threshold; and determining a cause of abnormality of the samples based on the positive and negative samples.

Abstract: The present disclosure relates to methods and apparatuses for processing an image, training an image recognition network and recognizing an image. The method of processing an image includes: obtaining a plurality of original images from an original image set, where at least one of the plurality of original images includes an annotation area; obtaining at least one first image by splicing the plurality of original images; for each of the at least one first image, adjusting a shape and/or size of the first image based on the plurality of original images to form a second image; obtaining respective positions of the at least one annotation area in the second image by converting respective positions of the at least one annotation area in the plurality of original images.

Abstract: A video processing method applied to a splicing screen is provided, including: dividing each frame of an initial video into multiple sub-images; and forming sub-videos using all the sub-images, the initial video and each sub-video including M frames, M being an integer greater than 1, and durations of individual frames of the sub-videos being the same, wherein i-th frames of all sub-videos are spliced into an i-th frame of the initial video, and a relative position of the i-th frame of any sub-video in the i-th frame of the initial video is the same as a relative position of any other frame of the sub-video in a corresponding frame of the initial video, where i is a variable whose value is a natural number from 1 to M. A dividing task distribution method, a computer-readable storage medium, a scheduling server, an execution server and a video processing system are provided.

Abstract: The present disclosure relates to a task processing method and device based on defect detection, a computer readable storage medium, and a task processing apparatus. The method includes receiving a detection task; determining a task type of the detection task; storing the detection task in a task queue if the task type is a target task type; and executing the detection task in a preset order and generating a feedback signal when a processor is idle. The detection task of the target task type includes an inference task and a training task. Executing the training task includes modifying configuration information according to a preset rule based on product information in the detection task; acquiring training data and an initial model according to the product information; and using the training data to train the initial model according to the configuration information to obtain a target model and store it in memory.

Abstract: A data processing method, comprising: acquiring a production record corresponding to each sample of a plurality of samples, the production record including process information, a production time corresponding to the process information, and an index value; determining a high-incidence time period of defects according to index values and production times corresponding to the process information in acquired production records of a plurality of samples; determining an influence degree of the process information on sudden defect according to the high-incidence time period of defects and the acquired production records.

Abstract: A method and apparatus for measuring the actual area of a defect, and a method and apparatus for testing a display panel. The method for measuring the actual area of a defect includes: acquiring a measurement image of a display panel, wherein the measurement image has a defect region; according to the measurement image, determining the area of defect pixels of the defect in the measurement image and determining the size of reference object pixels of a reference object in the measurement image; and according to the area of the defect pixels, the size of the reference object pixels and the actual size of the reference object, determining the actual area of the defect in the display panel.

Abstract: Provided is a method for querying questions. The method includes: acquiring input information of a user; acquiring intention information of the user based on the input information of the user; determining an answer generation rule; and generating, based on the input information and the intention information, a first answer in accordance with the answer generation rule, and providing the first answer to the user.

Abstract: The present disclosure relates to a task processing method and device based on defect detection, a computer readable storage medium, and a task processing apparatus . The method includes receiving a detection task; determining a task type of the detection task; storing the detection task in a task queue if the task type is a target task type; and executing the detection task in a preset order and generating a feedback signal when a processor is idle. The detection task of the target task type includes an inference task and a training task. Executing the training task includes modifying configuration information according to a preset rule based on product information in the detection task; acquiring training data and an initial model according to the product information; and using the training data to train the initial model according to the configuration information to obtain a target model and store it in memory.

Abstract: A video processing method applied to a splicing screen is provided, including: dividing each frame of an initial video into multiple sub-images; and forming sub-videos using all the sub-images, the initial video and each sub-video including M frames, M being an integer greater than 1, and durations of individual frames of the sub-videos being the same, wherein i-th frames of all sub-videos are spliced into an i-th frame of the initial video, and a relative position of the i-th frame of any sub-video in the i-th frame of the initial video is the same as a relative position of any other frame of the sub-video in a corresponding frame of the initial video, where i is a variable whose value is a natural number from 1 to M.A dividing task distribution method, a computer-readable storage medium, a scheduling server, an execution server and a video processing system are provided.

Abstract: A question recommendation method, a device, a system, an electronic device, and a non-volatile readable storage medium are provided. The question recommendation method includes: obtaining a candidate question set of a user, the candidate question set including a plurality of candidate questions; obtaining user behavior data, and obtaining a user interest parameter based on the user behavior data; based on the user interest parameter and the plurality of candidate questions, obtaining at least one similarity feature between each candidate question of the plurality of candidate questions and the user interest parameter; based on basic user information, the plurality of candidate questions, and the at least one similarity feature, sorting the plurality of candidate questions to obtain a question sequence; and based on an order of the question sequence, recommending at least one candidate question in the question sequence to the user.

Abstract: The present disclosure relates to methods and apparatuses for processing an image, training an image recognition network and recognizing an image. The method of processing an image includes: obtaining a plurality of original images from an original image set, where at least one of the plurality of original images includes an annotation area; obtaining at least one first image by splicing the plurality of original images; for each of the at least one first image, adjusting a shape and/or size of the first image based on the plurality of original images to form a second image; obtaining respective positions of the at least one annotation area in the second image by converting respective positions of the at least one annotation area in the plurality of original images.

Abstract: The present disclosure relates to an image data classification method, device and system, and relates to the field of computer technology.