公开(公告)号：US10552737B2

公开(公告)日：2020-02-04

申请号：US15851173

申请日：2017-12-21

Applicant: AXIS AB

Inventor： Robin Seibold ,  Jiandan Chen ,  Hanna Björgvinsdóttir ,  Martin Ljungqvist

IPC: G06N3/08 ,  G06K9/62

Abstract: Methods and apparatus, including computer program products, implementing and using techniques for configuring an artificial neural network to a particular surveillance situation. A number of object classes characteristic for the surveillance situation are selected. The object classes form a subset of the total number of object classes for which the artificial neural network is trained. A database is accessed that includes activation frequency values for the neurons within the artificial neural network. The activation frequency values are a function of the object class. Those neurons having activation frequency values lower than a threshold value for the subset of selected object classes are removed from the artificial neural network.

公开(公告)号：US20180181867A1

公开(公告)日：2018-06-28

申请号：US15851173

申请日：2017-12-21

Applicant: AXIS AB

Inventor： Robin Seibold ,  Jiandan Chen ,  Hanna Björgvinsdóttir ,  Martin Ljungqvist

IPC: G06N3/08 ,  G06K9/62

Abstract: Methods and apparatus, including computer program products, implementing and using techniques for configuring an artificial neural network to a particular surveillance situation. A number of object classes characteristic for the surveillance situation are selected. The object classes form a subset of the total number of object classes for which the artificial neural network is trained. A database is accessed that includes activation frequency values for the neurons within the artificial neural network. The activation frequency values are a function of the object class. Those neurons having activation frequency values lower than a threshold value for the subset of selected object classes are removed from the artificial neural network.