Abstract: A plurality of subimages of an image are generated based on output from a random number generator. Each subimage is input to a machine learning program trained to output an object classified in the subimage. When a number of subimages with a same classified object exceeds a threshold, an object in the image is identified as the classified object.

Abstract: A system subscribes to one or more inference topics to which inferences are published on behalf of trainable software models executing in a vehicle computing environment. The system receives inferences from the topics as the inferences are published to the topics and associates the inferences with one or more trainable software models to be monitored. Also, the system identifies instances of unexpected output based on comparison of received inferences, associated with a given model to be monitored, to expected inference values identified in a configuration file, stored in a vehicle memory and associated with the given model, and, responsive to identifying the unexpected output, devises a modification strategy for the model based on characteristics of the unexpected output.

Abstract: A system receives identification of a machine learning model, stored by a vehicle, that is ready for training. The system determines, based on a configuration file associated with the model, whether batch-based or live training is to be used to train the model and collects data for training, defined by a configuration file associated with the model. The system calls a learning as a service vehicle process to load a kernel and configures the kernel based on configuration data defined in the configuration file. The system receives notification from the learning as a service process that the training is complete. Additionally, the system validates a model, responsive to the notification including indication that training was successful, using a vehicle model validation process to test the model with live data before deployment by background execution of the model and saves a copy of the model for deployment responsive to successful validation.

Abstract: A vehicle system receives indication of a newly trained machine learning model designated for validation. The system load a copy of the model into shadow execution hardware, capable of background execution of the model and subscribes to one or more data topics to which input data for the model, gathered by a vehicle data gathering process, is published. The system executes the model in the background as the vehicle travels, using data published to the data topics and benchmarks output from the model to determine whether the model outperforms a prior version of the model, that represents the model prior to the model being newly trained, based on relative performance of both models compared to performance expectations defined in a configuration file stored by the vehicle. Also, the system, responsive to the model outperforming the prior version of the model based on the performance expectations defined by the configuration file, validates the model as suitable for deployment.

Abstract: A plurality of subimages of an image are generated based on output from a random number generator. Each subimage is input to a machine learning program trained to output an object classified in the subimage. When a number of subimages with a same classified object exceeds a threshold, an object in the image is identified as the classified object.

Abstract: Described herein are technologies pertaining to computing the solar irradiance distribution on a surface of a receiver in a concentrating solar power system or glint/glare emitted from a reflective entity. At least one camera captures images of the Sun and the entity of interest, wherein the images have pluralities of pixels having respective pluralities of intensity values. Based upon the intensity values of the pixels in the respective images, the solar irradiance distribution on the surface of the entity or glint/glare corresponding to the entity is computed.

Abstract: Described herein are technologies pertaining to computing the solar irradiance distribution on a surface of a receiver in a concentrating solar power system or glint/glare emitted from a reflective entity. At least one camera captures images of the Sun and the entity of interest, wherein the images have pluralities of pixels having respective pluralities of intensity values. Based upon the intensity values of the pixels in the respective images, the solar irradiance distribution on the surface of the entity or glint/glare corresponding to the entity is computed.

Abstract: Described herein are technologies pertaining to computing the solar irradiance distribution on a surface of a receiver in a concentrating solar power system or glint/glare emitted from a reflective entity. At least one camera captures images of the Sun and the entity of interest, wherein the images have pluralities of pixels having respective pluralities of intensity values. Based upon the intensity values of the pixels in the respective images, the solar irradiance distribution on the surface of the entity or glint/glare corresponding to the entity is computed.

Abstract: A curb climbing wheelchair system having left and right side attachments are designed to be attached to left and right side portions, respectively, of a standard wheelchair to enable a wheelchair occupant to climb a curb, bump or other obstruction without the aid of another individual. Each attachment includes a ramp extending from a telescoping arm that is designed to be attached, via a clamping system, to one side of the wheelchair. When not in use, the ramps are folded and stowed away on the sides of the wheelchair. During use, the ends of the ramps are placed on the curb to allow the wheelchair occupant to roll up the curb. To retrieve the ramps (now disposed behind the wheelchair), the wheelchair occupant moves the telescoping arms, if necessary with the aid of an attached circular handle, to lift the ramps thus allowing the wheelchair occupant to grab the ramps. The retrieved ramps then are stowed away until needed.

Abstract: A curb climbing wheelchair system having left and right side attachments are designed to be attached to left and right side portions, respectively, of a standard wheelchair to enable a wheelchair occupant to climb a curb, bump or other obstruction without the aid of another individual. Each attachment includes a ramp extending from a telescoping arm that is designed to be attached, via a clamping system, to one side of the wheelchair. When not in use, the ramps are folded and stowed away on the sides of the wheelchair. During use, the ends of the ramps are placed on the curb to allow the wheelchair occupant to roll up the curb. To retrieve the ramps (now disposed behind the wheelchair), the wheelchair occupant moves the telescoping arms, if necessary with the aid of an attached circular handle, to lift the ramps thus allowing the wheelchair occupant to grab the ramps. The retrieved ramps then are stowed away until needed.