Vehicles and related systems and methods are provided for classifying detected objects in a location-dependent manner using localized models in a federated learning environment. A method involves obtaining sensor data for a detected object external to the vehicle from a sensor of a vehicle, obtaining location data associated with the detected object, obtaining a local classification model associated with an object type, assigning the object type to the detected object based on an output by the local classification model as a function of the sensor data and the location data using the local classification model, and initiating an action at the vehicle responsive to assigning the object type to the detected object.

A counterfeit and imaging detection system includes a processor, a counterfeit product detection app, and a steganographic imaging model, electronically accessible by the counterfeit product detection app trained using image data and configured cause the processor to obtain a digital image of a physical product of a product line, the digital image captured by an imaging device and the digital image comprising pixel data, analyze the digital image to detect within the pixel data a batch code uniquely identifying a batch of the physical product of the product line, analyze the pixel data of the digital image to determine that the batch code is counterfeit, and augment a counterfeit list of batch codes to include the batch code, wherein the counterfeit list of batch codes remains electronically accessible to the counterfeit product detection app for one or more further counterfeit detection iterations.

A focus method and an image sensing apparatus are disclosed. The method includes capturing, by a plurality of event sensing pixels, event data of a targeted scene, wherein the event data indicates which pixels of the event sensing pixels have changes in light intensity, accumulating the event data for a predetermined time interval to obtain accumulated event data, determining whether a scene change occurs in the targeted scene according to the accumulated event data, obtaining one or more interest regions in the targeted scene according to the accumulated event data in response to the scene change, and providing at least one of the one or more interest regions for a focus operation. The image sensing apparatus comprises a plurality of image sensing pixels, a plurality of event sensing pixels, and a controller configured to perform said method.

A system, tracking an object within an environ, includes a hub with a processor instantiating a vision recognizer, a data store storing location data including a first location model, and a first camera which captures and provides, within a first field of view (FOV), a first image to the hub. The first image includes a first depiction of a first captured location, and the vision recognizer determines an object is present at the first location when the first depiction of the first captured location corresponds to the first location model. The first image depicts an element present within the first FOV, the data store further stores an image library record including a first object model, and the vision recognizer determines whether the object is present at the first location when the element depicted in the first image corresponds to the object as modeled by the first object model.

A system, tracking an object within an environ, includes a hub with a processor instantiating a vision recognizer, a data store storing location data including a first location model, and a first camera which captures and provides, within a first field of view (FOV), a first image to the hub. The first image includes a first depiction of a first captured location, and the vision recognizer determines an object is present at the first location when the first depiction of the first captured location corresponds to the first location model. The first image depicts an element present within the first FOV, the data store further stores an image library record including a first object model, and the vision recognizer determines whether the object is present at the first location when the element depicted in the first image corresponds to the object as modeled by the first object model.

The present invention relates to a method and system for facilitating access to recorded data. The system comprises an interface and a processing device. The interface is arranged to receive data and the processing device is arranged to separate the received data in data subsets, compress each data subset and assign an identifier to each compressed data subset, thereby creating data units each comprising a compressed data subset and an associated identifier, the processing device further being arranged to establish an index on the basis of the assigned identifiers.

Automated detection of features and/or parameters within an ocean environment using image data. In an embodiment, captured image data is received from ocean-facing camera(s) that are positioned to capture a region of an ocean environment. Feature(s) are identified within the captured image data, and parameter(s) are measured based on the identified feature(s). Then, when a request for data is received from a user system, the requested data is generated based on the parameter(s) and sent to the user system.

Techniques for prioritization of media related to an incident are provided. Confirmed incident related media may be retrieved, the confirmed incident related media having been confirmed as being associated with the incident. Artifacts of interest may be identified in the confirmed incident related media. Presence of the artifacts of interest in a plurality of received media may be determined. The plurality of received media may be prioritized based on the presence of the artifacts of interest.

Disclosed are systems, methods, and non-transitory computer-readable media for automatic image selection for online product catalogs. An image selection system gathers feature data for images of an item included in listings posted to an online marketplace. The image selection system uses the feature data as input in a machine learning model to determine probability scores indicating an estimated probability that each image is suitable to represent the item. The machine learning model is trained based on a set of training images of the item that have been labeled to indicate whether they are suitable to represent the image. The image selection system compares the probability scores and selects an image to represent the item as a stock image based on the comparison.

Disclosed herein are apparatuses and methods for providing evacuation guidance. An implementation may comprise identifying a person physically present in an environment requiring an evacuation. The implementation further includes detecting, using at least one sensor in the environment, a last known location of the person. The implementation further includes calculating an exit time for evacuating the environment based on the last known location. The implementation further includes monitoring, using at least one sensor located at an egress point of the environment, whether the person has evacuated the environment. The implementation further includes determining whether a current time has passed the exit time. The implementation further includes transmitting an alert to a device of the respective person in response to determining that the current time has passed the exit time and that the person has not evacuated the environment.