Abstract: A method of board lumber grading is performed in an industrial environment on a machine learning framework configured as an interface to a machine learning-based deep convolutional network that is trained end-to-end, pixels-to-pixels on semantic segmentation. The method uses deep learning techniques that are applied to semantic segmentation to delineate board lumber characteristics, including their sizes and boundaries.

Abstract: A method of board lumber (Table 2) grading is performed in an industrial environment on a machine learning framework (12) configured as an interface to a machine learning-based deep convolutional network (20) that is trained end-to-end, pixels-to-pixels on semantic segmentation. The method uses deep learning techniques that are applied to semantic segmentation to delineate board lumber characteristics (Table 1), including their sizes and boundaries.

Abstract: A pluggable migration framework can interface with a plurality of repositories that store metadata related to one or more applications. A user can customize the applications to suit the user's business requirements. The user can develop and test the customized applications in a source environment, and the customized features can be stored as metadata in one or more of the plurality of repositories. When the customized application is ready to be used by others, it can be migrated to a target environment. The pluggable migration framework can include an orchestrator that enables the user to export metadata from the plurality of repositories in the source environment, and import the metadata to a plurality of repositories in the target environment, without requiring the user to re-implement the custom features.

Abstract: A pluggable migration framework can interface with a plurality of repositories that store metadata related to one or more applications. A user can customize the applications to suit the user's business requirements. The user can develop and test the customized applications in a source environment, and the customized features can be stored as metadata in one or more of the plurality of repositories. When the customized application is ready to be used by others, it can be migrated to a target environment. The pluggable migration framework can include an orchestrator that enables the user to export metadata from the plurality of repositories in the source environment, and import the metadata to a plurality of repositories in the target environment, without requiring the user to re-implement the custom features.