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公开(公告)号:US20250086958A1
公开(公告)日:2025-03-13
申请号:US18728049
申请日:2022-12-16
Applicant: SRI International
Inventor: Richard J. Rohwer , Andrew C. Silberfarb
IPC: G06V10/82 , G06T7/246 , G06V10/24 , G06V10/764 , G06V10/776 , G06V20/70
Abstract: Techniques are disclosed for a soft logic block that can provide visual primitives to soft logic in coordination with a learned attention mechanism. In an example, computing system for object detection, the computing comprising processing circuitry and a storage device, wherein the processing circuitry has access to the storage device and is configured to execute a machine learning system comprising a placement neural network configured to process a patch of image data to generate local placement parameters for aligning a footprint in the patch to a template footprint; and a template comprising a backend network and the template footprint, the template configured to process a transformed footprint comprising the footprint in the patch transformed according to the local placement parameters, to generate a probability value quantifying a likelihood that a particular pattern is present in the footprint.
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公开(公告)号:US20240265266A1
公开(公告)日:2024-08-08
申请号:US18434435
申请日:2024-02-06
Applicant: SRI International
Inventor: Theodore Camus , Zachary Seymour , Bhoram Lee , Andrew C. Silberfarb , Supun Samarasekera , Jonathan Brookshire
Abstract: In general, techniques are described for coordinating actions of a plurality of agents or subsystems using a machine learning system that implements a Capability Graph Network (CGN). In an example, a method includes generating a control policy model comprising a plurality of nodes and a plurality of edges interconnecting the plurality of nodes, wherein the plurality of nodes represents a plurality of agents or subsystems and the plurality of edges represent information exchange between the plurality of agents or subsystems; and encoding agent behavior control policy within the control policy model for executing to coordinate a plurality of the actions of the plurality of agents or subsystems.
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