Abstract: Some embodiments employ a consensus-building procedure to train a multitask graph comprising a plurality of nodes interconnected by a plurality of edges, wherein each node is associated with a task of determining a set of node-specific attributes of a set of input data, and each edge comprises an AI module (e.g., neural network) configured to determine attributes of an end node according to attributes of a start node of the respective edge. Training fosters consensus between all edges converging to a node. The trained multitask graph may then be deployed in a threat detector configured to determine whether an input set of data is indicative of malice (e.g., malware, intrusion, online threat, etc.).

Abstract: An image processing system receives an image depicting a bundle of boards. The bundle of boards has a front face that is perpendicular to a long axis of boards and the image is captured at an angle relative to the long axis. The image processing system applies a homographic transformation to estimate a frontal view of the front face and identifies a plurality of divisions between rows in the estimate. For each adjacent pair of the plurality of divisions between rows, a plurality of vertical divisions is identified. The image processing system identifies a set of bounding boxes defined by pairs of adjacent divisions between rows and pairs of adjacent vertical divisions. The image processing system may filter and/or merge some bounding boxes to better match the bounding boxes to individual boards. Based on the bounding boxes, the image processing system determines the number of boards in the bundle.

Abstract: A computer-based system (e.g., a handheld device) is configured to detect, count, and measure logs in a stack. A user captures one or more images of the stack. Where multiple images are captured, the system creates a working image by stitching together portions of the image. The system identifies a contour indicating the outline of the stack in the working image and fits ellipses to the log faces in the working image. Information such as the number of logs, the volume of wood in the stack, and the average log diameter may be made available for presentation to the user.

Abstract: A computer-based system (e.g., a handheld device) is configured to detect, count, and measure logs in a stack. A user captures one or more images of the stack. Where multiple images are captured, the system creates a working image by stitching together portions of the image. The system identifies a contour indicating the outline of the stack in the working image and fits ellipses to the log faces in the working image. Information such as the number of logs, the volume of wood in the stack, and the average log diameter may be made available for presentation to the user.

Abstract: An image processing system receives an image depicting a bundle of boards. The bundle of boards has a front face that is perpendicular to a long axis of boards and the image is captured at an angle relative to the long axis. The image processing system applies a homographic transformation to estimate a frontal view of the front face and identifies a plurality of divisions between rows in the estimate. For each adjacent pair of the plurality of divisions between rows, a plurality of vertical divisions is identified. The image processing system identifies a set of bounding boxes defined by pairs of adjacent divisions between rows and pairs of adjacent vertical divisions. The image processing system may filter and/or merge some bounding boxes to better match the bounding boxes to individual boards. Based on the bounding boxes, the image processing system determines the number of boards in the bundle.

Abstract: An image processing system receives an image depicting a bundle of boards. The bundle of boards has a front face that is perpendicular to a long axis of boards and the image is captured at an angle relative to the long axis. The image processing system applies a homographic transformation to estimate a frontal view of the front face and identifies a plurality of divisions between rows in the estimate. For each adjacent pair of the plurality of divisions between rows, a plurality of vertical divisions is identified. The image processing system identifies a set of bounding boxes defined by pairs of adjacent divisions between rows and pairs of adjacent vertical divisions. The image processing system may filter and/or merge some bounding boxes to better match the bounding boxes to individual boards. Based on the bounding boxes, the image processing system determines the number of boards in the bundle.

Abstract: An image processing system receives an image depicting a bundle of boards. The bundle of boards has a front face that is perpendicular to a long axis of boards and the image is captured at an angle relative to the long axis. The image processing system applies a homographic transformation to estimate a frontal view of the front face and identifies a plurality of divisions between rows in the estimate. For each adjacent pair of the plurality of divisions between rows, a plurality of vertical divisions is identified. The image processing system identifies a set of bounding boxes defined by pairs of adjacent divisions between rows and pairs of adjacent vertical divisions. The image processing system may filter and/or merge some bounding boxes to better match the bounding boxes to individual boards. Based on the bounding boxes, the image processing system determines the number of boards in the bundle.