Abstract: An inter-device positional relationship estimation apparatus includes an analysis information acquisition unit that acquires time-series analysis information, a recommendation processing unit that estimates unanalyzed detailed information in time-series analysis information applying a predetermined recommendation algorithm, an initial map creation unit that calculates a neighborhood determination point indicating a degree of correlation of detailed information between fixed devices to create an initial map, and a device relationship map creation unit that calculates neighborhood points indicating a degree of correlation of detailed information between respective devices including a moving device or/and a new fixed device to calculate a detection probability and a movement time between devices and create a device relationship map.

Abstract: A method for measuring a growth height of a plant, an electronic device, and a storage medium are provided. The method controls a camera device to obtain a color image and a depth image of a plant to be detected. The color image is detected by a detection model which is pre-trained, and a plurality of detection boxes which includes a plurality of plants to be detected is obtained. The color image and the depth image are aligned to create an alignment image. A plurality of target boxes is acquired from the alignment image, and depth values of the plurality of target boxes are determined. The quantity of the target boxes and a height of one or more plants to be detected are determined, no manual operations are required.

Abstract: A computer-implemented method is provided for a mobile device to detect, by a camera of the mobile device, a plurality of checks; determine, by a processing unit of the mobile device, that the image of the plurality of checks is of sufficient quality; instruct, by a display of the mobile device, a user to take a photograph of the plurality of checks; crop, by the processing unit, the photograph of the plurality of checks into a plurality of images, wherein each of the plurality of images contains one of the plurality of checks; and transmit, by a transmitter of the mobile device, the plurality of images to a server via a network. The plurality of images may be transmitted individually (i.e., one at time), or alternatively, collectively and in one payload.

Abstract: Provided is a computer-implemented method for training a machine learning (ML) model using labelled and unlabelled data, the method comprising obtaining a set or training data comprising a set of labelled data items and a set of unlabelled data items, training a loss module of the ML model using labels in the set of labelled data items, to generate a trained loss module capable of estimating a likelihood of a label for a data item, and training a task module of the ML model using the loss module, the set of labelled data items, and the set of unlabelled data items, to generate a trained task module capable of making a prediction of a label for input data.

Abstract: A computer-implemented method estimates a course of a roadway in a surrounding area of a vehicle on the basis of a state function describing the course of a roadway. The state function includes a clothoid spline. The method includes providing surrounding-area measurement data describing the course of a roadway at a current position of the vehicle, the surrounding-area measurement data having at least one polynomial function. The method also includes transforming the state function and the surrounding-area measurement data into a common coordinate system. The method further includes adapting the state function on the basis of the surrounding-area measurement data in the common coordinate system.

Abstract: An image capture device with processors can execute a set of instructions stored in the system memory to: receive a plurality of time-sequenced images of the animal from the digital image sensor; determine, using an artificial intelligence module, a first birth in process from a first subset of images of the plurality of time-sequenced images of the animal; and determine an interval of time lapse between the first birth in process from the first subset of images of the plurality of time-sequenced images of the animal and a next birth in process from the next subset of images of the plurality of time-sequenced images of the animal, as determined using the artificial intelligence module, and when the interval of time lapse between the first birth in process and the next birth in process exceeds a predetermined amount trigger an action from an alert trigger.

Abstract: Systems and methods for identifying surgery tools of a robotic surgery system in surgery video based on robot kinematics are described. Kinematic data describing a position of a first robotic surgery arm including a surgery tool is used to determine a nominal position of the first robotic surgery arm. A search area within image data obtained during a robotic surgery from an endoscope attached to a second robotic surgery arm is determined based on the kinematic data and a nominal position of the surgery tool. The surgery tool is identified within the search area of the image data using an object detection technique.

Abstract: A method for determining a growth height of a plant, an electronic device, and storage medium are provided. The method includes controlling a camera device to capture a plant to be detected, and obtaining a color image and a depth image of the plant to be detected. The color image and the depth image are aligned and an alignment image is obtained. The color image is detected using a pre-trained mobilenet-ssd network, and a detection box including the plant to be detected is obtained. A depth value of each of pixel points in the detection box is determined, and target depth values are obtained. A mean value and a standard deviation of the target depth values are determined, and a height of the plant to be detected is determined. According to the method, accuracy of the height of the plant can be improved.

Abstract: An object amount calculation apparatus includes: a receiver configured to obtain a first three-dimensional model and a second three-dimensional model different from the first three-dimensional model, each of the first three-dimensional model and the second three-dimensional model representing a same space, each of the first three-dimensional model and the second three-dimensional model being constituted with regions having respective attributes; and a processor configured to: align the first three-dimensional model and the second three-dimensional model based on at least one attribute of the first three-dimensional model and the second three-dimensional model; calculate, for each of the attributes, a difference between the first three-dimensional model aligned and the second three-dimensional model aligned; and output (i) a total amount of differences corresponding to two or more attributes among the attributes and (ii) information on the two or more attributes.

Abstract: Provided is an image analysis unit which analyzes a captured image of a camera mounted on a mobile device, executes object identification of an image, and sets a label as an identification result to an image region; a low-confidence region extraction unit which extracts a region with low confidence of object identification from an image analysis result; and a label updating unit which updates a label of the low-confidence region on the basis of information received via a communication unit. The label updating unit updates a label in a case where a matching rate between an object region analyzed from information received via the communication unit and the low-confidence region is equal to or greater than a specified threshold.

Abstract: A system and method automatically orient geological core samples. The system comprises a camera, a core analyzer module, and a core sample rotation apparatus. The camera is configured to capture a reference image of a cross-section of a reference core sample from a well and to capture a sample image of a cross-section of the to-be-oriented core sample from the well. The core analyzer module comprises code executable in a hardware processor to process the sample image to substantially match the reference image, and to determine an orientation angle of the match. The core sample rotation apparatus is configured to orient the to-be-oriented core sample by the orientation angle. A method comprises steps performed during operation of the system.

Abstract: An image processing apparatus includes an image synthesizer configured to correct input images based on first-correction data to generate corrected images, and to generate a synthesized image by stitching the corrected images together, a determiner configured to determine whether the corrected images are appropriately stitched together in the synthesized image by using a first-trained model learned whether images are appropriately stitched together, a second-correction-data generator configured to generate second-correction data by supplying the input images to a second-trained model learned relationships between correction data used to correct source images to generate corrected images appropriately stitched together and the source images, and an image updater configured to output the synthesized image when a determination result of the determiner is affirmative and output an updated synthesized image generated by causing the image synthesizer to update the synthesized image based on the second-correction da

Abstract: A vehicle occupant monitoring apparatus includes an operation determination unit and an output unit. The operation determination unit is configured to process a captured image obtained by an imaging device configured to capture an image of an occupant in a vehicle. The operation determination unit is further configured to determine a non-contact operation provided by the occupant. The output unit is configured to output a control signal associated beforehand with the non-contact operation that is provided by the occupant and that is determined by the operation determination unit.

Abstract: Provided is a system and method for estimating the motion of a target inside a tissue based on surface deformation of the soft tissue. The system consists of an acquisition unit, a reference input unit, two surface extraction units, a target position extraction unit, a feature calculation unit, and a target motion estimation unit. The method includes: the acquisition unit acquires an image Ii of the soft tissue; the surface extraction unit extracts a surface fi of the soft tissue from Ii; the reference input unit acquires a reference image Iref of the soft tissue; the surface extraction unit and the target position extraction unit respectively extract a reference surface fref of the soft tissue and a target reference position tref from Iref, the feature calculation unit calculates deformation feature ?i of fi relative to fref, the target motion estimation unit estimates the target displacement based on ?i and tref.

Abstract: A system of automatically monitoring an electronic billboard to immediately responding a production abnormality and a method thereof are disclosed. In the system, a monitoring device performs an image pattern analysis on a monitoring image to analyze at least one analysis area, and captures the at least one analysis area as a to-be-analyzed image; at least one image analysis method is set to transform the to-be-analyzed image into an image characteristic according to an image pattern of the to-be-analyzed image. When a comparison between the image characteristic and a preset characteristic indicates an abnormality, a monitoring device generates, records and transmits a warning message and/or issues an alarm, thereby achieving the technical effect of automatically monitoring the electronic billboard and immediately responding a production abnormality.

Abstract: A CADx system for analysing medical images and determining if the images are acceptable for analysis, by determining if the images contain out-of-distribution input data is described. The CADx system comprises: an input circuit for receiving at least one medical image; a gatekeeper circuit for determining if the at least one received medical image contains out-of-distribution input data and so does not meet the requirements of the CADx system for acceptable images; and an output circuit to produce an output that is either a determination that the at least one received medical image contains out-of-distribution data and is not suitable for analysis by the CADx system, or a determination that the medical image is acceptable.

Abstract: One or more multi-layer systems are used to perform inference. A multi-layer system may correspond to a node that receives a set of sensory input data for hierarchical processing, and may be grouped to perform processing for sensory input data. Inference systems at lower layers of a multi-layer system pass representation of objects to inference systems at higher layers. Each inference system can perform inference and form their own versions of representations of objects, regardless of the level and layer of the inference systems. The set of candidate objects for each inference system is updated to those consistent with feature-location representations for the sensors as well as object representations at lower layers. The set of candidate objects is also updated to those consistent with candidate objects from other inference systems, such as inference systems at other layers of the hierarchy or inference systems included in other multi-layer systems.

Abstract: Embodiments relate to performing inference, such as object recognition, based on sensory inputs received from sensors and location information associated with the sensory inputs. The sensory inputs describe one or more features of the objects. The location information describes known or potential locations of the sensors generating the sensory inputs. An inference system learns representations of objects by characterizing a plurality of feature-location representations of the objects, and then performs inference by identifying or updating candidate objects consistent with feature-location representations observed from the sensory input data and location information. In one instance, the inference system learns representations of objects for each sensor. The set of candidate objects for each sensor is updated to those consistent with candidate objects for other sensors, as well as the observed feature-location representations for the sensor.

Abstract: A method of generating a virtual 3D model of a dental arch is provided. The method includes receiving intraoral scans of a dental arch, determining a first depth of a first intraoral 3D surface in a first intraoral scan, and determining a second depth of a second intraoral 3D surface in the first intraoral scan, and wherein there is a fixed distance between the first intraoral 3D surface and the second intraoral 3D surface in the first intraoral scan. The method further includes stitching together the intraoral scans and generating a virtual 3D model of the dental arch from the intraoral scans, wherein the fixed distance between the first intraoral 3D surface and the second intraoral 3D surface is included in the virtual 3D model.

Abstract: Disclosed are a profiling method and apparatus based on a personal region of interest. The profiling method includes determining a region of interest (ROI) indicative of an interest region of a user based on the profile of a person, and generating relationship information indicative of a relationship between a specific person and the user based on a degree of intimacy between persons and the ROI. The AI device and the AI system of the present disclosure may be associated with an artificial intelligence module, a drone (or unmanned aerial vehicle (UAV)), a robot, an augmented reality (AR) device, a virtual reality (VR) device, a device related to 5G service, etc.