Abstract: An example method for performing depth measurements with an image sensor comprises, for at least a first pixel, performing one or more continuous-wave phase measurements for the first pixel and performing a coded-modulation measurement for the first pixel. The method further comprises determining a mask value for the first pixel, based on the coded-modulation measurement, and applying the mask value to a distance value calculated from the one or more continuous-wave phase measurements, to obtain a masked distance value for the first pixel that has no ambiguity due to phase wrapping.

Abstract: An approach is provided for filtering imagery to train a feature detection model. The approach involves, for example, receiving a plurality of images. The plurality of images is classified as depicting a feature of interest. The approach also involves providing data for presenting a bulk arrangement of at least one subset of the plurality of images, wherein the bulk arrangement is based on a characteristic of the plurality of images (e.g., detection confidence, position, size, visual characteristic, etc. of the detected feature). The approach further involves initiating a filtering of the plurality of images based on the bulk arrangement and providing the filtered plurality of images as training data to train the feature detection model.

Abstract: Data obtained by computer processing device(s) includes human biological change data from event data stream(s) and dynamic marketplaces allowing for ranking change(s). The data can correlate biological change data with ranking statistics from an event such that the correlation identifies and measures a magnitude of change of human biological responses from data acquired from event data stream(s). The correlation of human biological change data and/or dynamic changing marketplace data with ranking statistics creates object(s) for storage and analysis within database(s), wherein the objects possess time synchronized responses before, during or after events.

Abstract: A movement distance calculation device includes: a first movement distance calculation unit which calculates a first movement distance of a movable body based on plural rotation speeds of plural wheels of the movable body and a steering angle of the movable body; a vector detection unit which detects a movement vector of an object included in the acquired images as defined herein; a second movement distance calculation unit which calculates a second movement distance of the movable body based on the movement vector; a first reliability determining unit which determines reliability of the calculated first movement distance as defined herein; a second reliability determining unit which determines reliability of the calculated second movement distance as defined herein; and a movement distance determining unit which determines a movement distance using at least one of the calculated first movement distance and the calculated second movement distance as defined herein.

Abstract: Discussed herein are systems, devices, and methods for automatic target recognition based on a non-visible input image. A method can include providing, as input to a first machine learning (ML) model for object classification, pixel data of a non-visible image, the first ML model including an encoder from a second ML model, the second ML model trained to generate a visible image representation of an input non-visible image, and receiving, from the first ML model, data indicating one or more objects present in the non-visible image.

Abstract: System and methods for identifying a brain condition of a patient subject to a plurality of disease states are provided, in some aspects, the method includes receiving imaging data associated with a patient's brain acquired using an imaging system, and constructing a classifier having signatures corresponding to a plurality of disease states. The method also includes applying the classifier to the imaging data to determine a degree to which the patient expresses at least one of the plurality of disease states, and determining a brain condition of the patient using the determined degree. The method further includes generating a report indicative of the brain condition of the patient.

Abstract: Systems and methods for part quality confidence are described. In some examples a part quality confidence system may receive inputs (e.g., via sensor measurements, operator input(s), etc.) related to one or more stages of a part assembly process. The inputs may be representative of certain feature characteristics of the part and/or one or more of the assembly stages. A computational engine of the system may determine one or more quality characteristics of the part based on the feature characteristics, and assign a quality metric to the part (and/or part assembly process) based on the quality characteristics. In some examples, a quality rating may be assigned to the part based on the quality metric, so as to provide an even simpler abstraction.

Abstract: A monitoring system, comprising: at least one device, comprising at least one processing circuitry configured for: receiving from at least one image sensor connected to the at least one processing circuitry, at least one digital image captured by the at least one image sensor; identifying a nature of at least one relationship between at least one first body part of at least one first person and at least one second body part of at least one second person, where the at least one first person and the at least one second person are identified in the at least one digital image; identifying at least one offending relationship according to the nature of the at least one relationship and a set of relationship rules; and outputting an indication of the at least one offending relationship.

Abstract: A method for sending early warning information, a storage medium and a terminal are provided. The method includes: calculating a target similarity between a first face image and a target face image when the first face image captured by an imaging device is acquired; and generating and sending early warning information corresponding to the first face image if the target similarity reaches a similarity threshold at the current moment; wherein, the similarity threshold is determined by a fluctuation degree value of a plurality of similarities in a similarity sample, the similarity in the similarity sample is a target similarity corresponding to a generated warning information, and the similarity sample is updated over. As a result, the accuracy in early warning may be improved.

Abstract: A poultry raising system includes: an imaging unit configured to capture an image of an inside of a poultry house; and a monitoring unit configured to determine a variation in density of chickens present in a particular region in the image captured by the imaging unit, and monitor the variation determined. The particular region is at least part of the image.

Abstract: A method of reducing radiation dose for radiology imaging modalities and nuclear medicine by using a convolutional network to generate a standard-dose nuclear medicine image from low-dose nuclear medicine image, where the network includes N convolution neural network (CNN) stages, where each stage includes M convolution layers having K×K kernels, where the network further includes an encoder-decoder structure having symmetry concatenate connections between corresponding stages, downsampling using pooling and upsampling using bilinear interpolation between the stages, where the network extracts multi-scale and high-level features from the low-dose image to simulate a high-dose image, and adding concatenate connections to the low-dose image to preserve local information and resolution of the high-dose image, the high-dose image includes a dose reduction factor (DRF) equal to 1 of a radio tracer in a patient, the low-dose PET image includes a DRF of at least 4 of the radio tracer in the patient.

Abstract: Metabolite profiles are generated from magnetic resonance images. These metabolite profiles indicate a topography of the metabolites in one or more anatomical regions. The magnetic resonance images can be metabolite images, such as those obtained using hyperpolarized 13C-MRI. The metabolite profiles can be generated by parcellating the magnetic resonance images into different regions, computing z-scores for those regions, and generating the metabolite profile based on the computed z-scores.

Abstract: A non-transitory computer-readable medium includes instructions that when executed by a processor cause the processor to perform a method for selecting available assignments for users based on mobile computing devices of the user. The method includes receiving an indication of at least one parameter of a mobile computing device associated with a user; accessing a plurality of available assignments, each assignment of the plurality of available assignments involving use of at least one mobile computing device; based on the at least one parameter of the mobile computing device associated with the user, selecting a subset of the plurality of available assignments; and offering the selected subset of the plurality of available assignments to the user.

Abstract: A system for automatically addressing detected conditions within the retail store is provided. The system may include at least one processor configured to receive a plurality of images depicting a plurality of products displayed on a plurality of store shelves; retrieve reference data specifying a desired state of the retail store; use the reference data to detect an indicator of a first service-improvement condition; use the reference data to detect an indicator of a second service-improvement; determine a first product-related task for addressing the first service-improvement condition; determine a second product-related task for addressing the second service-improvement condition; access a database storing information indicative of a first employee and a second employee on duty during a time interval over which the plurality of images was received; and assign the first product-related task to the first employee and assign the second product-related task to the second employee.

Abstract: System, methods, and other embodiments described herein relate to improving clustering of points within a point cloud. In one embodiment, a method includes grouping the points into cells of a grid. The grid divides an observed region of a surrounding environment associated with the point cloud into the cells. The method includes computing feature vectors for the cells that use cell features to characterize the points in the cells and relationships between the cells. The method includes analyzing the feature vectors according to a clustering model to identify clusters for the cells. The clustering model evaluates the cells to identify which of the cells belong to common entities. The method includes providing the clusters as assignments of the points to the entities depicted in the point cloud.

Abstract: An image captioning system and method is provided for generating a caption for an image. The image captioning system utilizes a policy network and a value network to generate the caption. The policy network serves as a local guidance and the value network serves as a global and lookahead guidance.

Abstract: An item identification method, system and electronic device are provided. The method includes: acquiring multi-frame images of the item by an image capturing device; processing the multi-frame images of the item to obtain position information and category information of the item in each frame image; acquiring auxiliary information of the item by an information capturing device; performing multi-modality fusion on the position information and the auxiliary information to obtain a fusion result; and determining an identification result of the item according to the category information and the fusion result. Through at least some embodiments of the present disclosure, a problem of low identification accuracy when identifying an item in the related art is partially solved.

Abstract: A method can include receiving (1) images of at least one subject and (2) at least one total mass value for the at least one subject. The method can further include executing a first machine learning model to identify joints of the at least one subject. The method can further include executing a second machine learning model to determine limbs of the at least one subject based on the joints and the images. The method can further include generating three-dimensional (3D) representations of a skeleton based on the joints and the limbs. The method can further include determining a torque value for each limb, based on at least one of a mass value and a linear acceleration value, or a torque inertia and an angular acceleration value. The method can further include generating a risk assessment report based on at least one torque value being above a predetermined threshold.

Abstract: A neural network system is proposed. The neural network can be trained by model-based reinforcement learning to select actions to be performed by an agent interacting with an environment, to perform a task in an attempt to achieve a specified result. The system may comprise at least one imagination core which receives a current observation characterizing a current state of the environment, and optionally historical observations, and which includes a model of the environment. The imagination core may be configured to output trajectory data in response to the current observation, and/or historical observations. The trajectory data comprising a sequence of future features of the environment imagined by the imagination core. The system may also include a rollout encoder to encode the features, and an output stage to receive data derived from the rollout embedding and to output action policy data for identifying an action based on the current observation.

Abstract: Disclosed herein include embodiments of a system, a device, and a method for sorting a plurality cells of a sample. A plurality of raw images comprising pixels of complex values in a frequency space can be generated from a plurality of channels of fluorescence intensity data of fluorescence emissions of fluorophores, the fluorescence emissions being elicited by fluorescence imaging using radiofrequency-multiplexed excitation in a temporal space. Spectral unmixing can be performed on the raw images prior to a sorting decision being made.