Abstract: An ultrasound emitter launches an ultrasonic signal into a diffuse medium such as tissue. The diffuse medium is illuminated with an infrared illumination signal. activating an ultrasound emitter to launch an ultrasonic signal into a diffuse medium. An infrared reference beam is interfered with an infrared exit signal having an infrared wavelength that is the same as the infrared illumination signal. An infrared image is captured of the interference of the infrared reference beam with the infrared exit signal.

Abstract: Techniques are disclosed for a combined machine learned (ML) model that may generate a track confidence metric associated with a track and/or a classification of an object. Techniques may include obtaining a track. The track, which may include object detections from one or more sensor data types and/or pipelines, may be input into a machine-learning (ML) model. The model may output a track confidence metric and a classification. In some examples, if the track confidence metric does not satisfy a threshold, the ML model may cause the suppression of the output of the track to a planning component of an autonomous vehicle.

Abstract: The method, system, and non-transitory computer-readable medium embodiments described herein provide for identifying invalid identification documents. In various embodiments, an application executing on a user device prompts the user device to transmit an image of the identification document. The application receives an image including the identification document in response to the identification document being within a field of view of a camera of the user device. The identification document includes a plurality of visual elements, and one or more visual elements of the plurality of visual elements are one or more invalidating marks. The application detects a predetermined pattern on the identification document in the image, the predetermined pattern formed from the one or more invalidating marks. The application determines that the identification document is invalid based on the detected predetermined pattern.

Abstract: Embodiments of a method and/or system, such as for characterizing at least one microorganism-related condition, can include: determining a set of associations (e.g., positive associations such as positive correlations, negative associations such as negative correlations, non-associations such as no correlation or minimal correlation, etc.) between a set of microorganism taxa and at least one microorganism-related condition; determining a set of reference features (e.g., reference abundance ranges, etc.) for the set of microorganism taxa; and determining one or more significance index metrics based on the set of associations and the set of reference features.

Abstract: The present invention provides a ranging method based on laser-line scanning imaging to effectively suppress interference of extreme weather on imaging. The method includes the following steps: acquiring priori reference images for a fixed laser-line scanning system, including respectively placing reference whiteboards at different distances, projecting line laser beams to the whiteboards, and acquiring the reference images by using a camera; placing a laser-line scanning device in a real scene, causing the laser-line scanning device to respectively emit line lasers at different angles, and acquiring an image at each scanning angle by using a camera; and performing fusion calculation on the acquired scanning image in the real scene and the priori reference images by using a ranging algorithm based on laser-line scanning, and extracting distance information of a surrounding object, to implement environment perception.

Abstract: Devices, methods, and program storage devices for training and leveraging machine learning (ML) models to use in image registration, especially on unaligned multispectral images, are disclosed, comprising: obtaining aligned multispectral image data; generating a first plurality of feature descriptors for features identified in the aligned multispectral image data; generating a training set of feature descriptor pairs based on the first plurality of feature descriptors; and training a ML model based on the training set of feature descriptor pairs, wherein the trained ML model is configured to determine matches between features in unaligned multispectral image data.

Abstract: Techniques are disclosed for characterizing and defining the location of a copy space in an image. A methodology implementing the techniques according to an embodiment includes applying a regression convolutional neural network (CNN) to an image. The regression CNN is configured to predict properties of the copy space such as size and type (natural or manufactured). The prediction is conditioned on a determination of the presence of the copy space in the image. The method further includes applying a segmentation CNN to the image. The segmentation CNN is configured to generate one or more pixel-level masks to define the location of copy spaces in the image, whether natural or manufactured, or to define the location of a background region of the image. The segmentation CNN may include a first stage comprising convolutional layers and a second stage comprising pairs of boundary refinement layers and bilinear up-sampling layers.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for labeling point clouds using distance field data. One of the methods includes obtaining a point cloud characterizing a region of the environment, the point cloud comprising a plurality of points; obtaining distance field data specifying, for each of a plurality of locations in the region of the environment, a distance from the location to a nearest static object in the environment; determining, using the distance field data and for each of the plurality of points, a respective distance from the point to a nearest static object in the environment to the point; and identifying, based on the respective distances for the plurality of points in the point cloud, one or more of the points as candidate dynamic object points that are likely to be measurements of a dynamic object in the environment.

Abstract: Provided herein are MD Codes, MD DYNA Codes, MD ASA, and Next Human system, and the methods of using them to diagnose and treat aesthetic conditions or disorders.

Abstract: Provided are a method for processing multimodal images, an apparatus, a device and a storage medium. Multiple types of vision sensors are disposed in first preset identity recognition scenario.

Abstract: In some embodiments, noise data may be used to train a neural network (or other prediction model). In some embodiments, input noise data may be obtained and provided to a prediction model to obtain an output related to the input noise data (e.g., the output being a prediction related to the input noise data). One or more target output indications may be provided as reference feedback to the prediction model to update one or more portions of the prediction model, wherein the one or more portions of the prediction model are updated based on the related output and the target indications. Subsequent to the portions of the prediction model being updated, a data item may be provided to the prediction model to obtain a prediction related to the data item (e.g., a different version of the data item, a location of an aspect in the data item, etc.).

Abstract: A detection device includes: a first detector which irradiates light onto the target object and detects light emitted from the target object; a first shape information generator which generates first shape information representing a first shape of the target object on the basis of a detection result of the first detector; and a second shape information generator which adds a second shape, which is based on information different from the detection result of the first detector, to the first shape, and which generates second shape information representing a shape including the first shape and the second shape.

Abstract: A bale monitoring system includes an imaging device that is operable to capture a stereoscopic image of a bale. A computing compares the stereoscopic image of the bale to a three-dimensional standard to identify a deviation of the bale from the three-dimensional standard. The computing device may then assign the bale a shape quality score based on the deviation of the bale from the three-dimensional standard. The shape quality score may indicate a magnitude of the deviation of the bale from the three-dimensional standard. Additionally, the stereoscopic image may be analyzed to identify characteristics of the bale, such as a broken wrap material or an improperly formed bale.

Abstract: An artificial intelligence (AI) system for geospatial height estimation may include a memory and a processor cooperating therewith to store a plurality of labeled predicted electro-optic (EO) image classified objects having respective elevation values associated therewith in a semantic label database, and train a model using trained EO imagery and the semantic label database. The processor may further estimate height values within new EO imagery for a geographic area based upon the trained model, and generate an estimated height map for the geographic area from the estimated height values and output the estimated height map on a display.

Abstract: According to one aspect, a long short-term memory (LSTM) cell for sensor fusion may include M number of forget gates, M number of input gates, and M number output gates. The M number of forget gates may receive M sets of sensor encoding data from M number of sensors and a shared hidden state. The M number of input gates may receive the corresponding M sets of sensor data and the shared hidden state. The M number output gates may generate M partial shared cell state outputs and M partial shared hidden state outputs based on the M sets of sensor encoding data, the shared hidden state, and a shared cell state.

Abstract: A method for analyzing microorganisms arranged in a sample is provided, the sample including a viability marker to modify an optical property of the microorganisms in different ways depending on whether they are dead or alive, the method including illumination of the sample and acquisition of an image of the latter by an image sensor, the image sensor then being exposed to an exposure light wave; determining positions of different microorganisms from the acquired image; applying a propagation operator to calculate at least one characteristic value of the exposure light wave at each radial position and at a plurality of distances from the detection plane representing a change in the characteristic value between the image sensor and the sample; and identifying living microorganisms according to each profile.

Abstract: A cancer cell detection device includes a computer with a database and a display and a microscope coupled to the computer. The microscope has a base upon which a biopsy sample can be placed. The device further includes a camera coupled to the microscope and computer. The camera is configured to capture images of the biopsy sample. The device also has a filter configured to attach to the microscope and a connection feature for connecting the computer to the camera and the filter. The computer further includes a processor that processes the images captured by the camera and classifies the images according to known variables stored in the database.

Abstract: Various approaches to ensuring safe operation of industrial machinery in a workcell include disposing multiple image sensors proximate to the workcell and acquiring, with at least some of the image sensors, the first set of images of the workcell; registering the sensors to each other based at least in part on the first set of images and, based at least in part on the registration, converting the first set of images to a common reference frame of the sensors; determining a transformation matrix for transforming the common reference frame of the sensors to a global frame of the workcell; registering the sensors to the industrial machinery; acquiring the second set of images during operation of the industrial machinery; and monitoring the industrial machinery during operation thereof based at least in part on the acquired second plurality of images, transformation, and registration of the sensors to the industrial machinery.

Abstract: A method of selecting a plant variety for cultivation in a target area includes selecting a selection score function; estimating values of a first set of environmental parameters for a predefined future period of time for the target area and receiving a set of phenotype information including phenotypic trait measurements for a first sub-set of a plurality of plant varieties and a set o environmental parameters for said first sub-set. Furthermore, the method includes determining a prediction model for the phenotypic traits; using the prediction model to output predictions for phenotypic traits for the plurality of chosen plant varieties; using the selection score function to compute selection score values; and selecting at least one plant variety to be cultivated in the target area from the plurality of chosen plant varieties, based the computed selection score values of the plurality of chosen plant varieties.

Abstract: Systems, methods, and non-transitory computer readable media configured to generate enhanced training information. Training information may be obtained. The training information may characterize behaviors of moving objects. The training information may be determined based on observations of the behaviors of the moving objects. Behavior information may be obtained. The behavior information may characterize a behavior of a given object. Enhanced training information may be generated by inserting the behavior information into the training information.