Ford Global Technolgoies, LLC

Vikas Rajendra

Raj Sohmshetty

Scott Mayberry

Sam Hoff

Tanveer Shaik

James Berg

Alan Beltran

Surya Gandikota

A method includes obtaining an authentic image of an assembly and a boundary label provided with the authentic image. The boundary label is associated with a selected region of the authentic image depicting a selected object. The method includes generating an augmented image based on the authentic image and an augmentation model employing one or more augmentation parameters, defining a model boundary label on a blank image at a region that correlates with the selected region of the authentic image, generating an augmented blank image based on the one or more augmentation parameters employed for the augmented image, identifying, as an augmented boundary label associated with augmented image, the model boundary label in the augmented blank image, and outputting an augmented image data, wherein the augmented image data incudes data indicative of the augmented image and of the augmented boundary label.

Method and system to augment images and labels to be compatible with various machine learning models

The disclosure generally pertains to systems and methods for determining preferred battery capacities. In an example method, a first set of data associated with scooter usage in a geographic area may be received. A first number of battery packs and a second number of battery packs for servicing the geographic area may be determined based at least on the first set of data, where the first number of battery packs has a first power capacity and the second number of battery packs has a second power capacity. A first cost associated with the first number of battery packs and a second cost associated with the second number of battery packs may be determined via a simulation model. The first cost may be determined to be lower than the second cost, and the first number of battery packs having the first power capacity may be selected to service the geographic area.

Systems and methods for determining preferred battery capacities

An identification apparatus for an equipped vehicle includes a camera configured to capture image data in a field of view directed to an exterior region proximate to the equipped vehicle and a controller in communication with the camera. The controller identifies an object in the image data and identifies a proportion of the object in response to pixels representing the object in the image data. The controller then communicates a notification indicating a trailing vehicle in response to the object approaching the camera in excess of a threshold.

System and method for approaching vehicle detection

A method includes defining, in an image, bounding boxes about an electrical connector assembly, identifying an edge of each of the bounding boxes, and determining one or more metrics based on the edge of each the bounding boxes, where the one or more metrics indicate a positional relationship between the edges of the bounding boxes. The method includes determining a state of the electrical connector assembly based on the one or more metrics and transmitting a notification based on the state.

Systems and methods for image-based electrical connector assembly detection

Systems and methods for protecting privacy for safety, comfort, and infotainment of one or more occupants of an autonomous vehicle are disclosed. For example, the system may capture image data indicative of an interior of the autonomous vehicle via one or more cameras integrated with the autonomous vehicle. The captured image data is then transformed to remove personal identification information of the one or more occupants, and the transformed image data may be analyzed to identify a concern, e.g., an occupant safety concern or a vehicle safety concern. The level of concern may be determined, and a mitigation strategy may be deployed based on the safety concern identified.

Systems and methods for ensuring privacy in an autonomous vehicle

An inspection apparatus includes a portable housing and at least one handle structure integrally formed with the portable housing. The inspection apparatus further includes a vision data system, a lighting system, a user interface system, a wireless communication system, and a controller. The vision data system includes one or more cameras provided on the first face of the portable housing. The vision data system is operable to capture component data. The lighting system is arranged with the vision data system at the first face. The lighting system includes diffused light emitting diode (LED) ring arranged around at least one of the one or more cameras. The manufacturing inspection apparatus is a stand-alone and all-in-one computing device. The manufacturing inspection apparatus processes and stores inspection data locally.

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Novi, MI, United States of America

Vikas Rajendra