Abstract: Controls within images of a user interface of a computer application are detected by way of region-based R-FCN and Faster R-CNN engines. Datasets comprising images containing application control, wherein the application controls include images of application where width is greater than height, width is equal to height and height is greater than width are retrieved. Each of the datasets is processed with the R-FCN and Faster R-CNN engines to generate a software configured to recognize, from an input image, application controls wherein the application controls are characterized by dimensions where width is greater than height, where width is substantially equal to height, and where height is greater than width.

Abstract: A system comprising a computer-readable storage medium storing at least one program and a method for determining, tracking, and anticipating risk in a manufacturing facility are presented. In example embodiments, the method includes generating a risk data model for the manufacturing facility based on correlations between historical staffing conditions of the manufacturing facility and deviations from existing manufacturing procedures. The method further includes receiving projected operational data that includes information related to anticipated future staffing conditions of the manufacturing facility. The method further includes calculating a risk score based on the projected operational data using the risk data model. The method further includes causing presentation of a user interface that includes a display of the risk score.

Abstract: A system comprising a computer-readable storage medium storing at least one program and a method for determining, tracking, and anticipating risk in a manufacturing facility are presented. In example embodiments, the method includes generating a risk data model for the manufacturing facility based on correlations between historical staffing conditions of the manufacturing facility and deviations from existing manufacturing procedures. The method further includes receiving projected operational data that includes information related to anticipated future staffing conditions of the manufacturing facility. The method further includes calculating a risk score based on the projected operational data using the risk data model. The method further includes causing presentation of a user interface that includes a display of the risk score.

Abstract: A system comprising a computer-readable storage medium storing at least one program and a method for determining, tracking, and anticipating risk in a manufacturing facility are presented. In example embodiments, the method includes generating a risk data model for the manufacturing facility based on correlations between historical staffing conditions of the manufacturing facility and deviations from existing manufacturing procedures. The method further includes receiving projected operational data that includes information related to anticipated future staffing conditions of the manufacturing facility. The method further includes calculating a risk score based on the projected operational data using the risk data model. The method further includes causing presentation of a user interface that includes a display of the risk score.

Abstract: A system comprising a computer-readable storage medium storing at least one program and a method for determining, tracking, and anticipating risk in a manufacturing facility are presented. In example embodiments, the method includes obtaining operational data associated with a manufacturing facility. The method further includes accessing a risk data model corresponding to the manufacturing facility, and calculating a risk score based on the current operational data using the risk data model. The method further includes causing presentation of a user interface that includes a display of the risk score to provide a user with a measure of risk at the manufacturing facility.