Abstract: The present disclosure belongs to the field of microbial technology, and in particular relates to a microbial agent for promoting root nodule number increase and root nodule nitrogenase activity increase in leguminous crops and use thereof. The microbial agent is compounded from 4 microbes including Bacillus amyloliquefaciens, Brevibacillus laterosporu, Bacillus mucilaginosus Krassilnikov, and Enterobacter ludwigii by separate fermentative cultivation, concentration and mixing. The microbial agent can effectively promote root nodule number increase and root nodule nitrogenase activity increase, promote crop growth, and improve crop yield and product quality.

Abstract: An image processing method includes: acquiring an input image of a teaching scenario; performing detection on the input image to determine a rectangular detection area that includes a blackboard-writing area; analyzing the rectangular detection area to determine a target area corresponding to the blackboard-writing area; determining four vertices of the target area; and according to the four vertices of the target area, performing coordinate transformation on the target area to obtain a corrected blackboard-writing area image.

Abstract: A method for identifying an individual of an oplegnathus punctatus based on a convolutional neural network is provided. Target initial positioning involves three continuous convolutional layers and an average pooling layer. A region of feature interest point is obtained, a hyperparameter candidate box is set to obtain a region, thereby obtaining an approximate position of a target object. II_Net backbone convolutional neural network includes six convolutional layers and four pooling layers, which includes a LeakyReLU activation function used as an activation function of the first convolutional layer, convolutional network layers of Alexnet and parameter data, and a maximum pooling layer of an overlapped pooling structure. Fully connected layers use a genetic algorithm to improve data transmission between layers. With the established model, identification of the individual of the oplegnathus punctatus is performed by using test data.

Abstract: An assembly system is provided for automotive lamps and an operation method thereof. In the invention, three kinds of function robots are responsible for the transmission work of the workpieces among various functional stations, which realizes automatic coating, fastening, and whole lamp performance testing, etc. Meanwhile, the invention provides an assembly system with a bilateral assembly line operating simultaneously.

Abstract: Suggested is a continuous process for the manufacture of urea urethanes, comprising or consisting of the following steps: (a) providing at least one monohydroxyl compound (a1); at least one diisocyanate compound (a2); at least one diamine compound (a3) optionally at least one isocyanate stabilizer (a4); at least one solvent (a5); optionally at least one anti-gelling agent (a6) (b) blending said components (a2) and (a4) to form a first pre-mix (b1); (c) feeding said component (a1) and said first pre-mix (b1) to a first continuous reactor to form an intermediate (b2); (d) blending said components (a3), (a5) and (a6) to form a second premix (b3); (e) feeding said intermediate (b2) and said second premix (b3) to a second continuous reactor to form the urea urethane; and (f) collecting the urea urethane from the second continuous reactor.

Abstract: An assembly system is provided for automotive lamps and an operation method thereof. The assembly system includes two kinds of functional robots and many functional stations, and it uses the functional robots to transfer workpieces between the various functional stations to realize automatic gluing, fastening and whole lamp performance testing, etc., thereby reducing the amount of manual intervention and improving process integration. Further, the assembly system may provide an assembly system with a two-sided assembly line operating simultaneously, which greatly improves the working efficiency of thereof.

Abstract: Disclosed is a method for detecting densely occluded fish based on a YOLOv5 network, belonging to the technical field of fish images. The method includes a data set establishment and processing part, a model training part and a model testing part; the data set establishment and processing part includes data collection of fish pictures, data labelling and data division of the fish pictures; and the data division is to divide data into a training set, a verification set and a test set.

Abstract: A first robot for handling at least one first workpiece in a first processing operation of the apparatus, a second robot cooperating with the first robot for processing the at least one first workpiece in the first processing operation, and at least one first workpiece holder for holding the at least one first workpiece during the first processing operation. In order to improve robot-assisted processing of workpieces which differ from one another, the first robot handles at least one second workpiece and the second robot processes the at least one second workpiece in a second processing operation of the apparatus. The first robot or the second robot in order, in a changeover operation of the apparatus, to replace the at least one first workpiece holder automatically by at least one second workpiece holder for holding the at least one second workpiece during the second processing operation.

Abstract: Disclosed is a method for detecting Ophiocephalus argus cantor under intra-class occulusion based on cross-scale layered feature fusion, including image collecting, image processing and network model, where collected images are labeled, image sizes are adjusted to obtain input images, and the input images are input into an object detection network, integrated by convolution and inserted into cross-scale layered feature fusion modules, characterized by including dividing all features input into the cross-scale layered feature fusion modules into n layers, composed of s feature mapping subsets, and fusing features of each feature mapping subset with that of other feature mapping subsets, and connecting; carrying out convolution operation, outputting training result; adjusting network parameters by a loss function to obtain parameters for a network model; inputting final output candidate boxes into a non-maximum suppression module to screen correct prediction boxes, so that prediction result is obtained.

Abstract: This application relates to Artificial intelligence and provides a method for training a classifier, one example method including: obtaining a first training sample, where the first training sample includes a corresponding semantic tag; obtaining a plurality of second training samples, where each of the second training samples includes a corresponding semantic tag; determining a target sample from the plurality of second training samples based on semantic similarities between the first training sample and the plurality of second training samples; and training the classifier based on the first training sample, the target sample, and a semantic similarity between the first training sample and the target sample.

Abstract: A handheld object recognition method includes obtaining location information of each of one or more detected objects in a to-be-recognized image; obtaining a first label of each detected object indicating a type of the detected object, wherein the type of the detected object is used to represent a handheld relationship of the detected object; obtaining a handheld object from the one or more detected objects based on the first label; and obtaining a recognition result of the handheld object in the to-be-recognized image based on the location information of the handheld object.

Abstract: A video generation method, may be applied to the field of image processing and video generation in the field of artificial intelligence. The method includes: receiving a video generation instruction, and obtaining text information and image information in response to the video generation instruction, where the text information includes one or more keywords, and the image information includes N images; obtaining, based on the one or more keywords, an image feature that is in each of the N images and that corresponds to the one or more keywords; and inputting the one or more keywords and image features of the N images into a target generator network to generate a target video, where the target video includes M images, and the M images are images that are generated based on the image features of the N images and that correspond to the one or more keywords.

Abstract: This application provides a method and apparatus for updating an object recognition model in the field of artificial intelligence. In the technical solution provided in this application, a target image and first voice information of a user are obtained. The first voice information indicates a first category of a target object in the target image. A feature library of a first object recognition model is updated based on the target image and the first voice information. The updated first object recognition model includes a feature of the target object and a first label indicating the first category, and the feature of the target object corresponds to the first label. A recognition rate of an object recognition model can be improved more easily according to the technical solution provided in this application.

Abstract: This application discloses an object recognition method and apparatus in the field of artificial intelligence. This application relates to the field of artificial intelligence, and specifically, to the field of computer vision. The method includes: obtaining one or more body regions of a to-be-recognized image; determining a saliency score of each of the one or more body regions; and when a saliency score of a body region A is greater than or equal to a categorization threshold, determining a feature vector of an object in the body region A based on a feature of the object in the body region A, and determining a category of the object in the body region A based on the feature vector of the object in the body region A and a category feature vector in a feature library, where the body region A is any one of the one or more body regions.

Abstract: A method for identifying an individual of an oplegnathus punctatus based on a convolutional neural network is provided. Target initial positioning involves three continuous convolutional layers and an average pooling layer. A region of feature interest point is obtained, a hyperparameter candidate box is set to obtain a region, thereby obtaining an approximate position of a target object. II_Net backbone convolutional neural network includes six convolutional layers and four pooling layers, which includes a LeakyReLU activation function used as an activation function of the first convolutional layer, convolutional network layers of Alexnet and parameter data, and a maximum pooling layer of an overlapped pooling structure. Fully connected layers use a genetic algorithm to improve data transmission between layers. With the established model, identification of the individual of the oplegnathus punctatus is performed by using test data.

Abstract: An assembly system is provided for automotive lamps and an operation method thereof. The assembly system includes two kinds of functional robots and many functional stations, and it uses the functional robots to transfer workpieces between the various functional stations to realize automatic gluing, fastening and whole lamp performance testing, etc., thereby reducing the amount of manual intervention and improving process integration. Further, the assembly system may provide an assembly system with a two-sided assembly line operating simultaneously, which greatly improves the working efficiency of thereof.

Abstract: An assembly system is provided for automotive lamps and an operation method thereof. In the invention, three kinds of function robots are responsible for the transmission work of the workpieces among various functional stations, which realizes automatic coating, fastening, and whole lamp performance testing, etc., and reduces the amount of manual intervention and improves the process integration. By setting a reasonable turnover area, the waiting time caused by the difference of transmission rate among processes is shortened. Meanwhile, the invention provides an assembly system with a bilateral assembly line operating simultaneously, which greatly improves the efficiency of the assembly system.

Abstract: A first robot for handling at least one first workpiece in a first processing operation of the apparatus, a second robot cooperating with the first robot for processing the at least one first workpiece in the first processing operation, and at least one first workpiece holder for holding the at least one first workpiece during the first processing operation. In order to improve robot-assisted processing of workpieces which differ from one another, the first robot handles at least one second workpiece and the second robot processes the at least one second workpiece in a second processing operation of the apparatus. The first robot or the second robot in order, in a changeover operation of the apparatus, to replace the at least one first workpiece holder automatically by at least one second workpiece holder for holding the at least one second workpiece during the second processing operation.

Abstract: The present disclosure relates to a constant liquid level gasification furnace with a waste boiler comprising: a housing; an upper portion of the housing is defined as a gasification section, a middle portion of the housing is defined as a radiant section, and a lower portion of the housing is defined as a quenching section. The gasification section internally includes a membrane type water-cooled wall, wherein the inner region defined by the membrane type water-cooled wall is a gasification chamber. The radiant section internally includes a built-in radiant waste boiler assembly, wherein the internal region defined by the built-in radiant waste boiler assembly is a radiant chamber. The region defined by the quenching section is a quenching chamber.

Abstract: A system includes a database that stores information associated with a medication located in a base station. The information includes an indication of whether a container of the medication was returned to the base station subsequent to the medication being administered. A control module communicates with the base station, determines when the medication is retrieved from the base station, determines whether the container of the medication is returned to the base station, and updates the information stored in the database when the container of the medication is returned to the base station.