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: The present disclosure provides a detection method. The detection method includes inputting an image to be detected into a detection model being pre-constructed and detecting the image to be detected. The detection model includes a defect classification identification sub-model configured to identify a classification of a defect in the image to be detected, and the defect classification identification sub-model comprises a plurality of base models and a secondary model. The present disclosure further provides an electronic device and a non-transitory computer-readable storage medium.

Abstract: An inference computing apparatus comprises at least one processor and a memory with program instructions stored therein, the program instructions can be executed by the at least one processor to cause the inference computing apparatus to perform the following operations: receiving a first inference model from a model training apparatus, the first inference model being obtained through a model training by the model training apparatus based on a first training sample library, the first training sample library comprising training samples from historical data generated in a manufacturing stage; performing an inference computing on data to be processed generated in the manufacturing stage based on the first inference model to obtain the inference result which is sent to a user-side device; and evaluating performance of the first inference model to determine whether the first inference model needs to be updated, and if yes, updating the first inference model.

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: An image marking method, apparatus and system, which relates to the technical field of image processing. The present disclosure includes, when the working mode of the first client is a first mode, receiving a first marking task assigned by a second client, on the condition that the image marking approach is the first marking approach, according to a neural network model, determining a first marking result corresponding to the first original image; on the condition that the image marking approach is the second marking approach, according to an unsupervised algorithm model, determining a second marking result corresponding to the first original image; on the condition that the image marking approach is the third marking approach, receiving a third marking result inputted by a user into the first original image; and sending a target marking result to the second client.

Abstract: The present disclosure provides a creation method, an information processing method, a storage method, an electronic device and a storage medium. The creation method includes: acquiring a creation request for creating the supply chain management system, wherein the creation request contains a business information related to creating the supply chain management system; and creating the supply chain management system according to the business information and a blockchain basic architecture, in response to the creation request, wherein, the blockchain basic architecture includes an interface layer, a management layer, a core layer and a base layer, the supply chain management system includes a main chain system and a plurality of parallel chain systems connected to the main chain system, each of the parallel chain systems corresponds to a business scenario, and an information sharing between the plurality of parallel chain systems is achieved based on the main chain system.

Abstract: A method and a device for processing product manufacturing messages, and an electronic device are disclosed. The method for processing product manufacturing messages includes: monitoring a plurality of product manufacturing messages; establishing a product defect analysis task queue based on the plurality of product manufacturing messages; distributing product defect analysis tasks to product manufacturing assisting devices based on the product defect analysis task queue, wherein the product defect analysis tasks include a task of identifying product defect content based on a defect identification model; wherein the product defect content includes any one or more of: product defect type, product defect location, and product defect size.

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: A method for determining a correlation degree, an apparatus for determining a correlation degree, an electronic device, and a computer-readable storage medium. The method includes: acquiring measurement information and defect information on a display panel, wherein the measurement information includes a measurement value and a measurement location for a measurement indicator, and the defect information includes a defect type; determining an influence weight of the measurement indicator having the measurement value at the measurement location on the defect information of the defect type; and determining a correlation coefficient between the influence weight and the measurement value, and determining a correlation degree between the measurement information and the defect information according to the correlation coefficient.

Abstract: The present disclosure provides a production programming system based on a nonlinear program model, including: a distributed storage device and an analysis device, wherein the analysis device includes a processor configured to obtain production record information; construct the nonlinear program model based on the production record information; and solve the nonlinear program model to obtain first feasible solutions. The nonlinear program model includes a constraint condition that satisfies process requirements and an objective function indicating pressure equilibrium across the same device set, and each of the first feasible solutions is configured to indicate a production program. The present disclosure further provides a production programming method and a computer-readable storage medium which can improve efficiency and reduce device idleness rate.

Abstract: A computer-implemented method for defect analysis is provided. The computer-implemented method includes calculating a plurality of weight-of-evidence (WOE) scores respectively for a plurality of device operations with respect to defects occurred during a fabrication period, a higher WOE score indicating a higher correlation between a defect and a device operation; and ranking the plurality of WOE scores to obtain a list of selected device operations highly correlated with the defects occurred during the fabrication period, device operations in the list of selected device operations having a WOE score greater than a first threshold score. A respective one of the plurality of device operations is a respective device defined by a respective operation site at which the respective device perform a respective operation.

Abstract: A computer-implemented method for defect analysis is provided. The computer-implemented method includes calculating a plurality of weight-of-evidence (WOE) scores respectively for a plurality of device operations with respect to detects occurred during a fabrication period, a higher WOE score indicating a higher correlation between a defect and a device operation; and ranking the plurality of WOE scores to obtain a list of selected device operations highly correlated with the defects occurred during the fabrication period, device operations in the list of selected device operations having a WOE score greater than a first threshold score. A respective one of the plurality of device operations is a respective device defined by a respective operation site at which the respective device perform a respective operation.

Abstract: A method and a device for processing product manufacturing messages, and an electronic device are disclosed. The method for processing product manufacturing messages includes: monitoring a plurality of product manufacturing messages; establishing a product defect analysis task queue based on the plurality of product manufacturing messages; distributing product defect analysis tasks to product manufacturing assisting devices based on the product defect analysis task queue, wherein the product defect analysis tasks include a task of identifying product defect content based on a defect identification model; wherein the product defect content includes any one or more of: product defect type, product defect location, and product defect size.

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: 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: The present disclosure provides a detection method. The detection method includes inputting an image to be detected into a detection model being pre-constructed and detecting the image to be detected. The detection model includes a defect classification identification sub-model configured to identify a classification of a defect in the image to be detected, and the defect classification identification sub-model comprises a plurality of base models and a secondary model. The present disclosure further provides an electronic device and a non-transitory computer-readable storage medium.

Abstract: The present disclosure provides a detection device of a display panel. The detection device includes: an image receiver configured to receive a detection image of a display panel to be detected; a detector configured to input the detection image of the display panel to be detected into a detection model and generate a detection result by the detection model, the detection model is pre-constructed and configured to detect the display panel. The disclosure also provides a detection method of the display panel, an electronic device and a computer readable medium.

Abstract: A distributed computing system for product defect analysis is disclosed. The distributed computing system for product defect analysis includes a computing cluster for processing product manufacturing messages, a computing cluster for identifying product defect, a product image database, and a client device.