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662 results about "First class" patented technology

In database modeling, a first class item is one that has an identity independent of any other item. The identity allows the item to persist when its attributes change, and allows other items to claim relationships with the item.

Prediction by collective likelihood from emerging patterns

A system, method and computer program product for determining whether a test sample is in a first or a second class of data (for example: cancerous or normal), comprising: extracting a plurality of emerging patterns from a training data set, creating a first and second list containing respectively, a frequency of occurrence of each emerging pattern that has a non-zero occurrence in the first and in the second class of data; using a fixed number of emerging patterns, calculating a first and second score derived respectively from the frequencies of emerging patterns in the first list that also occur in the test data, and from the frequencies of emerging patterns in the second list that also occur in the test data; and deducing whether the test sample is categorized in the first or the second class of data by selecting the higher of the first and the second score.
Owner:AGENCY FOR SCI TECH & RES

Object versioning

A repository contains multiple versions of an object, and any version of the object can be modified by a user, as and when necessary. A table for one object (“first object”) that is contained in another object (“second object”) has at least two columns, namely one column for a minimum version of the second object and another column for a maximum version of the second object. If a number of versions of the first object are responsive to a query, then one version of the first object is selected if a version of the second object that is responsive to the query happens to be in the range defined by the just-described minimum version number and the maximum version number. Depending on the embodiment, the second object can be an immediate parent of the first object, or can be an ancestor (also called “first class object”) of the first object that is not contained in any other object. In some embodiments, one or more attributes of the first object are stored in a first table along with a unique identifier and a version number. In addition, information on relations of the first object to other objects as well as an identity of a configuration (to which the current version of the first object belongs) are stored in a second table. Therefore, a pair of tables are used for each object, so as to decouple information that defines an object from information on relationships of the object. If a change happens in just the relationship of an object then no change is made to the table containing the definition of the object. Similarly, if a change happens in just the definition of the object, then no change is made to the table containing the relations of the object. Moreover, when a change happens to an object, if the object has a number of ancestors and decendants only an immediate parent of the object is updated, thereby to eliminate a versioning chain reaction (i.e. other objects are not affected).
Owner:ORACLE INT CORP

Method for constructing semantic map on line by utilizing fusion of laser radar and visual sensor

The invention relates to a method for constructing a semantic map on line by utilizing fusion of a laser radar and a visual sensor. The method comprises the following steps: acquiring an initialized grid map of a current vehicle, and acquiring distance measurement data corresponding to the laser radar and image data corresponding to the visual sensor; performing target detection processing on theranging data of the laser radar to obtain multi-attribute information of a plurality of first-class detection targets; performing feature extraction and matching on the image data of the visual sensorto obtain multi-attribute information of a plurality of second-class detection targets; fusing the multi-attribute information of the first type of detection targets and the second type of detectiontargets, importing the fused multi-attribute information of the detection targets into a Redis database, generating a high-dimensional grid map serving as a semantic map, and storing the multi-attribute information of each detection target in the high-dimensional grid map in a dynamic database table mode. According to the method, the multi-dimensional semantic information of the dynamic and staticenvironments around the vehicle can be represented online in real time.
Owner:廊坊和易生活网络科技股份有限公司

Content classification method and device, computer equipment and storage medium

The invention relates to a content classification method and a device, a computer device and a storage medium. The method comprises the steps of obtaining a target feature vector corresponding to to-be-classified target content; obtaining a target classification model obtained by training, wherein the target classification model comprises a first classification model and a second classification model; inputting the target feature vector into a first classification model to obtain a first content category corresponding to the target content, the first content category being a content category corresponding to the first classification hierarchy; obtaining first category feature information corresponding to the first classification hierarchy; inputting the first category feature information and the target feature vector into a second classification model to obtain a second content category corresponding to the target content, the second content category being a content category corresponding to a second classification level, and the level of the second classification level being lower than the level of the first classification level; and taking the first content category and the second content category as classification results corresponding to the target content. The method can improve the content classification accuracy.
Owner:TENCENT TECH (SHENZHEN) CO LTD

Object versioning

A repository contains multiple versions of an object, and any version of the object can be modified by a user, as and when necessary. A table for one object (“first object”) that is contained in another object (“second object”) has at least two columns, namely one column for a minimum version of the second object and another column for a maximum version of the second object. If a number of versions of the first object are responsive to a query, then one version of the first object is selected if a version of the second object that is responsive to the query happens to be in the range defined by the just-described minimum version number and the maximum version number. Depending on the embodiment, the second object can be an immediate parent of the first object, or can be an ancestor (also called “first class object”) of the first object that is not contained in any other object. In some embodiments, one or more attributes of the first object are stored in a first table along with a unique identifier and a version number. In addition, information on relations of the first object to other objects as well as an identity of a configuration (to which the current version of the first object belongs) are stored in a second table. Therefore, a pair of tables are used for each object, so as to decouple information that defines an object from information on relationships of the object. If a change happens in just the relationship of an object then no change is made to the table containing the definition of the object. Similarly, if a change happens in just the definition of the object, then no change is made to the table containing the relations of the object. Moreover, when a change happens to an object, if the object has a number of ancestors and decendants only an immediate parent of the object is updated, thereby to eliminate a versioning chain reaction (i.e. other objects are not affected).
Owner:ORACLE INT CORP

Multi-scale rotating ship target detection algorithm

The invention provides a multi-scale rotating ship target detection algorithm. The algorithm comprises the following steps: acquiring a multi-scale feature map of an input image, wherein the multi-scale feature map comprises a first-class scale feature map, a second-class scale feature map and a third-class scale feature map of which the scales are sequentially increased; performing feature fusionon the multi-scale feature map by adopting a feature pyramid network, wherein the feature pyramid network adopts a ResNet residual network as a basic framework; inputting the feature map output by the feature pyramid network into a region suggestion network through a 3 * 3 convolution layer, classifying each anchor frame by adopting the region suggestion network according to a set classificationjudgment condition, endowing each anchor frame with parameter coordinates, and obtaining a rotating boundary frame based on parameter coordinate regression; performing adaptive region-of-interest alignment on a rotation bounding box generated by the region suggestion network to obtain a high-quality feature map; and screening the candidate boxes of the high-quality feature map according to a set rotation non-maximum suppression constraint condition to obtain a detection target.
Owner:PLA STRATEGIC SUPPORT FORCE INFORMATION ENG UNIV PLA SSF IEU

Information recommendation method, device and equipment and computer readable storage medium

The embodiment of the invention provides an information recommendation method, device and equipment and a computer readable storage medium, and relates to the technical field of artificial intelligence. The method comprises the steps of obtaining at least one first type of feature and at least one second type of feature of each piece of to-be-recommended information in a to-be-recommended information set, and performing feature cross processing on the at least one first type of feature to obtain a first prediction score; performing feature fusion processing on the at least one second type of features to obtain a second prediction score; performing prediction result transformation processing on the first prediction score and the second prediction score to obtain a tendency score of the to-be-recommended information; and recommending at least one piece of to-be-recommended information in the to-be-recommended information set to a target object according to the tendency score of each piece of to-be-recommended information. Through the embodiment of the invention, the popularity degree of the to-be-recommended information on the specific crowd can be described more accurately, and theinformation recommendation effect on the specific crowd is improved.
Owner:TENCENT TECH (SHENZHEN) CO LTD

File system establishing method and device

ActiveCN103678428ASolve the technical problem of not being able to create a file system on multiple storage devicesSolve the technical problem that the block storage bodies of multiple storage devices cannot be managed togetherSpecial data processing applicationsFile system functionsComputer hardwareFile system
The invention discloses a file system establishing method and device which are used for solving the technical problem that one file system can not be established on a plurality of storage devices and are applied to an electronic device. The electronic device at least comprises a first storage device and a second storage device; the first storage device and the second storage device are respectively provided with at least one subarea, and each subarea is provided with a plurality of storage blocks which are divided into first-class storage blocks and second-class storage blocks; the first-class storage blocks are used for storing control information, and the second-class storage blocks are used for storing data; information relevant to a first file system of established file systems, attribute information of all the second-class storage blocks in the first storage device and attribute information of all the second-class storage blocks in the second storage device are stored in the first-class storage blocks in each subarea of the first storage device and the first-class storage blocks in each subarea of the second storage device.
Owner:LENOVO (BEIJING) CO LTD

Knowledge graph expansion method, electronic equipment and storage medium

The embodiment of the invention relates to the technical field of knowledge maps, and discloses a knowledge graph expansion method, electronic equipment and a storage medium. The method comprises thefollowing steps: obtaining a keyword, finding an ontology where the keyword is located in a preset database, and locating the keyword according to the ontology where the keyword is located and the knowledge map. Obtaining a first class of statements and a second class of statements in to-be-processed text data, marking a first triple corresponding to the first class of statements according to theknowledge graph, and training by utilizing the first class of statements marked with the first triple to learn an association relationship between the first class of statements and the first triple, obtaining a relationship identification model, identifying the second class of statements by using the relationship identification model, determining a second triple corresponding to the second class of statements, and finally adding the second triple corresponding to the second class of statements to the knowledge graph. That is to say, triples in a certain field can be automatically extracted through keywords in the field and added into the knowledge graph, and therefore the knowledge graph is expanded.
Owner:深圳数联天下智能科技有限公司

Weak supervision semantic segmentation method and application thereof

The invention belongs to the technical field of computer vision, and particularly discloses a weak supervision semantic segmentation method and an application. The method comprises that: a pre-trainedsemantic erasure type region expansion classification network used for weak supervision semantic segmentation is adopted, first-stage feature extraction and high-level semantic integration classification are sequentially carried out on a picture to be semantically segmented, and a first class response graph corresponding to the picture is obtained; an area with high responsivity in the first category response diagram is erased, and second-stage high-level semantic integration classification is performed on the erased category response diagram to obtain a second category response diagram; andthe corresponding positions of the first category response diagram and the second category response diagram are added and fused to obtain a fused category response diagram, and background threshold segmentation processing is performed on the fused category response diagram to obtain a category segmentation region diagram. The erasure type region expansion classification network structure is greatly simplified, the expansion effect is good, the region expansion exploration efficiency is greatly improved, and the weak supervision semantic segmentation effect is further enhanced.
Owner:HUAZHONG UNIV OF SCI & TECH
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