公开(公告)号：US12147909B2

公开(公告)日：2024-11-19

申请号：US18491817

申请日：2023-10-23

Applicant: ZHEJIANG LAB

Inventor： Feng Lin ,  Yunhe Pan

IPC: G06N5/022 ,  G06F40/30 ,  G06V10/77 ,  G06V10/80 ,  G06V40/20

Abstract: A method and an apparatus for cross-media corresponding knowledge generation. The method comprises: generating a second knowledge unit of a second medium according to a first knowledge unit of a predefined first medium; generating a first feature parameter vector corresponding to the first knowledge unit and a second feature parameter vector corresponding to the second knowledge unit; mapping the first feature parameter vector and the second feature parameter vector to a corresponding two-dimensional spherical feature surface to obtain a first feature point of the first feature parameter vector on the corresponding two-dimensional spherical feature surface and a second feature point of the second feature parameter vector on the corresponding two-dimensional spherical feature surface; indexing the first feature point and the second feature point to obtain a first index and a second index; and generating a bidirectional index corresponding relationship between the first knowledge unit and the second knowledge unit.

公开(公告)号：US12106589B2

公开(公告)日：2024-10-01

申请号：US18491818

申请日：2023-10-23

Applicant: ZHEJIANG LAB

Inventor： Feng Lin ,  Yunhe Pan

IPC: G06V20/70 ,  G06F40/30 ,  G16H30/40

CPC classification number: G06V20/70 ,  G06F40/30 ,  G16H30/40 ,  G06V2201/03

Abstract: A cross-media knowledge semantic representation method and apparatus. The method comprises: performing data acquisition according to a preset semantic description; inputting data information of a topological structure acquired by the data acquisition into a preset stack of an automat corresponding to the semantic description, the finite state set is used for indicating states included in the automat, and the input vocabulary list is used for indicating vocabularies included in the automat; mapping the data information by the automat to obtain key frames corresponding respectively to substructures and/or branches of a target object acquired by the data acquisition; and generating a visual semantic representation of the topological structure according to the key frames corresponding respectively to the substructures and/or branches of the target object acquired by the data acquisition, such that cross-media knowledge alignment is realized.

公开(公告)号：US11934887B1

公开(公告)日：2024-03-19

申请号：US18466384

申请日：2023-09-13

Applicant: ZHEJIANG LAB

Inventor： Hongsheng Wang ,  Fei Wu ,  Guang Chen ,  Feng Lin

IPC: G06F9/50 ,  G06F8/41

CPC classification number: G06F9/5072 ,  G06F8/41 ,  G06F9/5066 ,  G06F2209/5016 ,  G06F2209/5017

Abstract: The present disclosure discloses a distributed model compilation system. A master node of the system determines the logic calculation graph of the model based on model information, divides the logic calculation graph into multiple logic calculation sub-graphs, generates a distributing message for each logic calculation sub-graph, and then transmits the distributing message to a slave node. Each of the slave nodes allocates a local computing resource to compile the logic calculation sub-graph based on the received distributing message, and transmits compilation completion information to the master node. The master node determines the completion of model compilation based on the compilation completion information returned by each slave node, and executes the target work based on the compiled model.

公开(公告)号：US12039361B1

公开(公告)日：2024-07-16

申请号：US18494002

申请日：2023-10-25

Applicant: ZHEJIANG LAB

Inventor： Hongsheng Wang ,  Guang Chen ,  Fei Wu ,  Feng Lin

IPC: G06F9/48

CPC classification number: G06F9/48

Abstract: The present disclosure discloses a method for executing a task. The method includes: a master computing device node in a computing cluster system receives a task code of a to-be-executed task; the master computing device node divides the to-be-executed task into subtasks, and for each of the subtasks, the master computing device node determines operators required to execute the subtask based on the task code; the master computing device node respectively distributes the subtasks to computing nodes in the computing cluster system, such that for each of the computing nodes, the computing node generates an executable task subgraph for the computing node based on the operators required to execute the subtask distributed to the computing node and data transmission relationships between the operators required to execute the subtask distributed to the computing node, and runs the executable task subgraph to execute the to-be-executed task.