A computer-implemented method for determining image similarity includes determining, by a first neural network, a first feature value associated with a first characteristic of a first product based on an image of the first product. The method also includes determining, by a second neural network, a second feature value associated with a second characteristic of the first product based on the image of the first product. The method further involves calculating a first vector space distance between the first feature value and a third feature value associated with the first characteristic of a second product, and calculating a second vector space distance between the second feature value and a fourth feature value associated with the second characteristic of the second product. Additionally, the method includes determining a similarity value based on the first vector space distance and the second vector space distance.

A computer-implemented method, computer program product, and computing system for automated clinical documentation is executed on a computing device and includes obtaining encounter information of a user encounter. The encounter information is processed to generate an encounter transcript. At least a portion of the encounter transcript is processed to populate at least a portion of a record associated with the user encounter.

A computer-implemented method, computer program product, and computing system for automating an intake process is executed on a computing device and includes prompting a user to provide encounter information via a virtual assistant during a pre-visit portion of a user encounter. Encounter information is obtained from the user in response to the prompting by the virtual assistant.

A computer-implemented method, computer program product, and computing system for automating a follow-up process is executed on a computing device and includes prompting a user to provide encounter information via a virtual assistant during a post-visit portion of a user encounter. Encounter information is obtained from the user in response to the prompting by the virtual assistant.

A computer-implemented method, computer program product, and computing system for automating a monitoring process is executed on a computing device and includes obtaining encounter information of a user encounter. The encounter information is processed to determine if the encounter information is indicative of a potential situation. An inquiry is initiated concerning the potential situation.

This application provides an object recognition method and apparatus, and a storage medium, and relates to the technical field of image recognition. The object recognition method includes: receiving an image of an object to be recognized; inputting the image of the object to be recognized into a pre-trained image feature extractor to obtain a first feature vector of the image of the object to be recognized; and determining category information of the object to be recognized according to the first feature vector of the image of the object to be recognized as well as image feature vectors in an image database, wherein the image database includes image information of a plurality of objects.

Disclosed is a fundus image quality evaluation method based on multi-source and multi-scale feature fusion, comprising following steps: S1, acquiring multi-source fundus images, labeling the multi-source fundus images with four evaluation dimensions of brightness, blur, contrast and overall image quality, and forming training samples with the fundus image and labeling labels; S2, constructing a fundus image quality evaluation network including a feature extraction module, a fusion module, an attention module and an evaluation module; S3, training the fundus image quality evaluation network by using training samples to obtain a fundus image quality evaluation model; and S4: inputting fundus images to be measured into the fundus image quality evaluation model, and outputting quality evaluation results through calculation. Also provided is a fundus image quality evaluation device based on above method.

Methods, systems, and articles of manufacture to improve image recognition searching are disclosed. In some embodiments, a first document image of a known object is used to generate one or more other document images of the same object by applying one or more techniques for synthetically generating images. The synthetically generated images correspond to different variations in conditions under which a potential query image might be captured. Extracted features from an initial image of a known object and features extracted from the one or more synthetically generated images are stored, along with their locations, as part of a common model of the known object. In other embodiments, image recognition search effectiveness is improved by transforming the location of features of multiple images of a same known object into a common coordinate system. This can enhance the accuracy of certain aspects of existing image search/recognition techniques including, for example, geometric verification.

One embodiment provides a method, including: receiving, from a client, (i) a task of annotating information, (ii) a set of instructions for performing the task, and (iii) client annotations for a subset of the information within the task; assigning the subset to a plurality of annotators; obtaining (i) annotator annotations for the subset and (ii) a response time for providing the annotator annotation for each piece of information within the subset; identifying improvements to the set of instructions by (i) comparing the annotator annotations to the client annotations and (ii) identifying discrepancies made by the annotators in view of the response time; and generating a new set of instructions, wherein the generating comprises (i) identifying at least one feature of the information that distinguishes correctly annotated information from incorrectly annotated information and (ii) generating an instruction from the at least one feature.

Disclosed are an image retrieval method, an image retrieval apparatus, an image retrieval device and a computer-readable storage medium, wherein the image retrieval method including: extracting global features of an input image and obtaining a global feature code based on the global features; extracting content features of the input image and obtaining a content feature code based on the content features; splicing the global feature code with the content feature code to obtain a composite feature code of the input image; comparing the composite feature code with alternative feature codes in a feature code library to obtain an image retrieval result. By comprehensively considering the global features and the content features of the input image in the image retrieval process, the accuracy and retrieval efficiency of the retrieval results can be improved.

Real time location systems are provided including one or more ultra-wideband (UWB) sensors positioned in an environment; one or more image capture sensors positioned in the environment; and at least one UWB tag associated with an object in the environment to provide a tagged item in the environment. The one or more UWB sensors and the one or more image capture sensors are integrated into at least one location device. The at one location device includes a UWB location device, a combination UWB/camera location device and/or a camera location device. A location of the tagged item is tracked using the at least one location device. and wherein a location of the tagged item is tracked using the at least one location device.

A mobile object control method including: recognizing physical objects near a mobile object and a route shape; generating a target trajectory based on a result of the recognition; causing the mobile object to travel autonomously along the target trajectory; and determining that an abnormality has occurred in a control system for causing the mobile object to travel autonomously by performing the recognition when a degree of deviation between a reference target trajectory determined by the route shape and serving as a reference for generating the target trajectory and the target trajectory is greater than or equal to a first reference degree and output a determination result.

Disclosed are methods and devices related to autonomous driving. In one aspect, a method is disclosed. The method includes determining three-dimensional bounding indicators for one or more first objects in road target information captured by a light detection and ranging (LIDAR) sensor; determining camera bounding indicators for one or more second objects in road image information captured by a camera sensor; processing the road image information to generate a camera matrix; determining projected bounding indicators from the camera matrix and the three-dimensional bounding indicators; determining, from the projected bounding indicators and the camera bounding indicators, associations between the one or more first objects and the one or more second objects to generate combined target information; and applying, by the autonomous driving system, the combined target information to produce a vehicle control signal.