Boe Technology Group Co., Ltd.

Beijing Zhongxiangying Technology Co., Ltd.

Zhaoyue Li

Hong Wang

Dong Chai

Yaoping Wang

Meijuan Zhang

Yuanyuan Lu

Yongzhang Liu

Wangqiang He

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.

Method and device for processing product manufacturing messages, electronic device, and computer-readable storage medium

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.

Detection method, electronic device and non-transitory computer-readable storage medium

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.

Inference computing apparatus, model training apparatus, inference computing system

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.

Image annotation method, device and system

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.

Defect detection task processing method, device, apparatus and storage medium

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.

Detection device of display panel and detection method thereof, electronic device and readable medium

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.

Distributed computing system for product defect analysis

The application provides an image detection method, an image detection apparatus, and a patterning control method, the image detection method including: identifying an input image to obtain image feature data of the input image; comparing the image feature data with preset image feature data in a preset image feature database to obtain deviation data of the input image; wherein the input image is a pattern image of a patterned structure. By intelligently detecting the pattern image of the patterned structure, the accuracy of the detection is improved, thereby reducing the labor input cost.

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Beijing, China

Zhaoyue Li