Abstract: An excrement judgement system according to the embodiment including: an acquisition unit that acquires image information on an image in which excrement excreted in a defecation action per time is captured; a determination unit that determines properties of a plurality of stools included in the image information and stool amounts corresponding to the properties of the plurality of stools; and an outputting unit that associates the properties of the plurality of stools and the stool amounts corresponding to the properties of the plurality of stools that are determined by the determination unit, and outputs the associated properties and stool amounts to a device to be displayed.

Abstract: Soundfield signals such as e.g. Ambisonics carry a representation of a desired sound field. The Ambisonics format is based on spherical harmonic decomposition of the soundfield, and Higher Order Ambisonics (HOA) uses spherical harmonics of at least 2nd order. However, commonly used loudspeaker setups are irregular and lead to problems in decoder design. A method for improved decoding an audio soundfield representation for audio playback comprises calculating a panning function (W) using a geometrical method based on the positions of a plurality of loudspeakers and a plurality of source directions, calculating a mode matrix (?) from the loudspeaker positions, calculating a pseudo-inverse mode matrix (?+) and decoding the audio soundfield representation. The decoding is based on a decode matrix (D) that is obtained from the panning function (W) and the pseudo-inverse mode matrix (?+).

Abstract: In one embodiment, a diagnosis support apparatus includes: an input circuit configured to acquire a first medical image; and processing circuitry configured to generate a second medical image from the first medical image in such a manner that information included in the second medical image is reduced from information included in the first medical image, extract auxiliary information from the first medical image, and perform inference of a disease by using the second medical image and the auxiliary information.

Abstract: A trailer angle determination system for a vehicle is provided. The trailer angle determination system has a sensing unit for sensing a trailer connected to the vehicle and an evaluation unit. The sensing unit is arranged outside of the center of the vehicle and toward the trailer, and the distance between the sensing unit and the center of the vehicle is known. The trailer has symmetrical feature pairs with respect to a longitudinal axis of symmetry of the trailer. The sensing unit is designed to sense the symmetrical feature pairs of the trailer. The evaluation unit is designed to determine the angle between the trailer and the vehicle based on the sensed symmetrical feature pairs of the trailer and the known distance between the sensing unit and the center of the vehicle.

Abstract: A method of vertical planar surface detection includes identifying, at an electronic device, a plurality of feature points of an environment proximate the electronic device based on imagery captured at the electronic device and based on received non-visual pose information obtained from non-visual sensors. The electronic device queries the plurality of feature points to identify one or more planar surfaces in the imagery captured at the electronic device. Further, the electronic device computes a plurality of oriented point vectors associated with the one or more planar surfaces. A vertical planar surface is detected based at least in part on one or more of the plurality of oriented point vectors being aligned in a direction perpendicular to gravity within a predetermined threshold.

Abstract: Systems and techniques for automatic digital parameter adjustment are described that leverage insights learned from an image set to automatically predict parameter values for an input item of digital visual content. To do so, the automatic digital parameter adjustment techniques described herein captures visual and contextual features of digital visual content to determine balanced visual output in a range of visual scenes and settings. The visual and contextual features of digital visual content are used to train a parameter adjustment model through machine learning techniques that captures feature patterns and interactions. The parameter adjustment model exploits these feature interactions to determine visually pleasing parameter values for an input item of digital visual content. The predicted parameter values are output, allowing further adjustment to the parameter values.

Abstract: Systems and methods for determining object intentions through visual attributes are provided. A method can include determining, by a computing system, one or more regions of interest. The regions of interest can be associated with surrounding environment of a first vehicle. The method can include determining, by a computing system, spatial features and temporal features associated with the regions of interest. The spatial features can be indicative of a vehicle orientation associated with a vehicle of interest. The temporal features can be indicative of a semantic state associated with signal lights of the vehicle of interest. The method can include determining, by the computing system, a vehicle intention. The vehicle intention can be based on the spatial and temporal features. The method can include initiating, by the computing system, an action. The action can be based on the vehicle intention.

Abstract: A body information acquisition device includes: a skeleton point detection unit configured to detect a skeleton point of a person included in a captured image; a body information acquisition unit configured to acquire body information of the person based on detection of the skeleton point; and an imaging state determination unit configured to determine whether an imaging state of the person reflected in the captured image corresponds to a specific imaging state specified based on a predetermined evaluation index value, in which the body information acquisition unit does not acquire the body information based on the detection of the skeleton point when the imaging state corresponds to the specific imaging state.

Abstract: Methods, computer readable media, and devices for exceeding the limits of visual-linguistic multi-task learning are disclosed. One method may include identifying a multi-modal multi-task classification dataset including a plurality of data examples, creating a transformer machine learning model to predict a plurality of categorical attributes of a product, and training the transformer machine learning model based on the multi-modal multi-task classification dataset using an alpha decay schedule and dynamically allocating task-specific parameters for at least one of the plurality of task-specific classification heads based on task complexity.

Abstract: Using a combination of image recognition, deep learning, and expert rules, disclosed systems and methods automatically identify, assess and estimate damage to vehicles based on input vehicle images. Analysis includes determinations as to type of damage, extent of damage and absolute size of damage. Disclosed embodiments include techniques of homography, allometry and semantic segmentation combined with more conventional object recognition technologies such as R-CNN in order to provide greater precision, more detailed analysis at lower computational cost.

Abstract: For one embodiment of the present invention, a method of object detection and part segmentation is described. The method includes generating a three-dimensional (3D) point cloud including a plurality of points in a volume of a space of the point cloud based on receiving point cloud dat. The method further includes obtaining, with a global transformer, a set of global feature tokens and local feature points of the 3D point cloud, enforcing with an attention mechanism information flow across the set of global feature tokens and local feature point, and generating, with the global transformer, a set of new global feature tokens and new local feature points with modeled global context information.

Abstract: Described are systems and methods that use one or more two-dimensional (“2D”) body images of a body to determine body fat measurements of that body. For example, a standard 2D camera of a portable device, such as a cell phone, tablet, laptop, etc., may be used to generate one or more 2D body images of a user. Those 2D body images, or image, may be processed using the disclosed implementations to determine a body fat measurement of the body represented in the image.

Abstract: Digital imaging systems and methods are described for analyzing pixel data of an image of a shaving stroke for determining pressure being applied to a user's skin. A plurality of training images of a plurality of individuals are aggregated, each of the training images comprising pixel data of a respective individual when shaving with a shaving razor. A pressure model, trained with the pixel data, is operable to determine pressure being applied to the respective individual's skin. An image of a user when shaving with the shaving razor is received and analyzed, by the pressure model, to determine a user-specific pressure being applied to the user's skin by the shaving razor when a user shaving stroke is taken. A user-specific electronic recommendation to address at least one feature identifiable within the pixel data is generated and rendered, on a display screen of a user computing device.

Abstract: A data analytics platform is provided for forecasting future states of commodities and other assets, based on processing of both textual and numerical data sources. The platform includes a multi-layer machine learning-based model that extracts sentiment from textual data in a natural language processing engine, evaluates numerical data in a time-series analysis, and generates an initial forecast for the commodity or asset being analyzed. The platform includes multiple applications of neural networks to develop augmented forecasts from further analysis of relevant information as it is collected. These include commodity-specific neural networks designed to continually develop taxonomies used to process commodity sentiment, and applications of reinforcement learning, symbolic networks, and unsupervised meta learning to improve overall performance and accuracy of the forecasts generated.

Abstract: In aspects, a visitor interaction system is described for interacting with visitors. The visitor interaction system can obtain video data, identify an approach of a person, and determine an identity of the person. Further, the visitor interaction system can determine that the person belongs to a respective visitor group of a plurality of visitor groups. Each of the plurality of visitor groups corresponds to a response model that includes a plurality of response actions. At least one of the response actions includes an autonomous response action. The visitor interaction system can also identify a response model corresponding to the respective visitor group and initiate an autonomous response action associated with the response model. The visitor interaction system can then send a report message to the user via a client device.

Abstract: Methods and systems are presented for detecting a boundary of a document within a digital image. Upon receiving an image, the image is converted into a binary image. One or more kernel-based transformations are performed on the binary image using a horizontal kernel and a vertical kernel. A plurality of edges are identified based on the one or more kernel-based transformations. The plurality of edges includes a plurality of horizontal edges and a plurality of vertical edges. Multiple quadrilaterals are constructed using different combinations of horizontal edges and vertical edges from the plurality of edges. A particular quadrilateral is selected from the multiple quadrilaterals based on how well the edges fit the perimeters of the quadrilaterals. The selected quadrilateral is used to define a boundary of the document within the digital image.

Abstract: The present disclosure describes an image processor of a display device. The image processing includes a pre-processor, a segmentation processor, and a correction processor. The pre-processor performs spatial filtering on an input image signal and output a line image signal. The segmentation processor classifies a class of the line image signal and outputting a segmentation signal representing the class. The correction processor corrects the segmentation signal based on the line image signal. Additionally, the correction processor detects a class boundary of the segmentation signal, detects an edge within an edge region of the line image signal corresponding to the class boundary, and corrects the segmentation signal based on the detected edge.

Abstract: Generating a prediction for at least one implant size for use in arthroplasty is disclosed. Patient demographic factors are received and processed to generate at least one implant size prediction. The processing includes accessing procedure information representing joint replacement procedures previously performed for a plurality of patients and implant information representing types and sizes of implants from a plurality of manufacturers and determining, as a function of at least one statistical model and the accessed procedural information and implant information, unadjusted probabilities of implant size recommendations in a range of implant sizes. At least one processor is further configured for providing, in a graphical user interface operating on at least one user computing device, information representing the respective implant size recommendations and unadjusted probabilities.

Abstract: Systems and methods for electromagnetic (EM) distortion detection and compensation are disclosed. In one aspect, the system includes an instrument, the system configured to: determine a reference position of the distal end of the instrument at a first time based on EM location data, determine that the distal end of the instrument at a second time is static, and determine that the EM location data at the second time is indicative of a position of the distal end of the instrument having changed from the reference position by greater than a threshold distance. The system is further configured to: determine a current offset based on the distance between the position at the second time and the reference position at the first time, and determine a compensated position of the distal end of the instrument based on the EM location data and the current offset.

Abstract: An embodiment in accordance with the present invention provides a miniature microscope capable of performing in vivo, real-time imaging of multiple organ sites in awake and behaving animals (e.g. rodents). A microscope according to the present invention includes multiple optical contrast mechanisms (i.e. contrast arising from neural, hemodynamic and other physiological components). Exemplary contrast mechanisms include, but are not limited to fluorescence, hemoglobin level, deoxyhemoglobin level, and blood flow. The microscope is fully adaptable to in vitro and ex vivo imaging, can be customized to concurrently image at variable magnifications, conduct optogenetic/electrical/chemical stimulations, drug delivery, microdialysis, accompanied by electrical signal recording, wireless image transmission and charging.