The present invention relates to methods and systems that utilize the production vehicles to develop new perception features related to new sensor hardware as well as new algorithms for existing sensors by using federated learning. To achieve this, the production vehicle's own worldview is post-processed and used as a reference, towards which the output of the software (SW) or hardware (HW) under development is compared. Through this comparison, a cost function can be calculated and an update of the SW parameters can be locally updated according to this cost function.

An ophthalmologic apparatus of an embodiment example includes a front image acquiring device, a first search processor, and a second search processor. The front image acquiring device is configured to acquire a front image of a fundus of a subject's eye. The first search processor is configured to search for an interested region corresponding to an interested site of the fundus based on a brightness variation in the front image. The second search processor is configured to search for the interested region by template matching between the front image and a template image in the event that the interested region has not been detected by the first search processor.

A method to correct for drift in an electronic device is described. The method comprises determining a first center pose of the electronic device; tracking, using a sensor in conjunction with computer vision operating on a processor, at least one key point within a scene when the first center pose is within a tolerance with respect to a reported center pose; determining a derived center poser based upon the first center pose and the at least one key point; disabling the sensor for a predetermined time; determining, after the predetermined time, whether a second center pose is within the tolerance with respect to the derived center pose; tracking, using the sensor, the at least one key point when the second center pose is within the tolerance with respect to the derived center pose; and adjusting the second center pose when there is a difference between the second center pose and the derived center pose.

The present disclosure provides an intelligent cataloging method for all-media news based on multi-modal information fusion understanding, which obtains multi-modal fusion features by unified representation and fusion understanding of video information, voice information, subtitle bar information, and character information in the all-media news, and realizes automatic slicing, automatic cataloging description, and automatic scene classification of news using the multi-modal fusion features. The beneficial effect of the present disclosure is that it realizes the complete process of automatic comprehensive cataloging for the all-media news, and improves the accuracy and generalization of the cataloging method, and greatly reduces the manual cataloging time by generating stripping marks, news cataloging descriptions, news classification labels, news keywords, and news characters based on the fusion of multi-modes of video, audio, and text.

The present disclosure relates to a method for displaying an interactive interface, a method for generating an interactive interface, and electronic devices thereof. By acquiring an image of a target object in a live streaming interface; and acquiring an interactive interface for interacting with the target object by performing a fusion process on the image and a dynamic effect material, wherein all or a part of the image is occluded in an interactive interface, the interactive interface is displayed in the live streaming interface.

Techniques are disclosed to facilitate, in autonomous vehicles, the robust detection and classification of objects in a scene using a static sensors in conjunction with event-based sensors. A trained system architecture may be implemented, and the fusion of both sensors thus allows for the consideration of scenes with overexposure, scenes with underexposure, as well as scenes in which there is no movement. In doing so, the autonomous vehicle may detect and classify objects in conditions in which each sensor, if operating separately, would not otherwise be able to classify (or classify with high uncertainty) due to the sensing environment.

An apparatus for controlling remote parking in a vehicle is provided. The apparatus includes an ultrasonic sensor that measures a distance from the vehicle to an obstruction and a receiver that receives a surround view monitoring (SVM) image. A controller executes remote parking of the vehicle by selectively using the distance from the obstruction, the distance being measured by the ultrasonic sensor, and the SVM image received by the receiver.

The technology disclosed relates to authenticating users using a plurality of non-deterministic registration biometric inputs. During registration, a plurality of non-deterministic biometric inputs are given as input to a trained machine learning model to generate sets of feature vectors. The non-deterministic biometric inputs can include a plurality of face images and a plurality of voice samples of a user. A characteristic identity vector for the user can be determined by averaging feature vectors. During authentication, a plurality of non-deterministic biometric inputs are given as input to a trained machine learning model to generate a set of authentication feature vectors. The sets of feature vectors are projected onto a surface of a hyper-sphere. The system can authenticate the user when a cosine distance between the authentication feature vector and a characteristic identity vector for the user is less than a pre-determined threshold.

This application relates to an adaptive inference system and an operation method therefor. In one aspect, the system includes a user terminal for collecting multi-modal information including at least visual information, voice information and text information. The system may also include an inference support device for receiving the multi-modal information from the user terminal, and inferring the intention of a user on the basis of pre-stored history information related to the user terminal, individualized information and the multi-modal information.

A light is shined on a specular surface of an inspected object at a fixed position. Light is reflected directly from the surface into a fixed camera. Multiple images are taken as the light source moves. Images are fused into a single image. This invention takes a single image and generates several defect detection images using several distinct image processing sequences. Each defect detection image alone could be used to identify when defects are located under a camera pixel, but the several images are combined to create a feature vector that can be used as an input to a pattern classifier. The pattern classifier may be trained to achieve superior defect detection results by combining several detection images.