Disclosed are methods, systems, and articles of manufacture for performing a process on biological samples. An analysis of biological samples in multiple regions of interest in a microfluidic device and a timeline correlated with the analysis may be identified. One or more region-of-interest types for the multiple regions of interest may be determined; and multiple characteristics may be determined for the biological samples based at least in part upon the one or more region-of-interest types. Associated data that respectively correspond to the multiple regions of interest in a user interface for at least a portion of the biological samples in the user interface based at least in part upon the multiple identifiers and the timeline. A count of the biological samples in a region of interest may be determined based at least in part upon a class or type of data using a convolutional neural network (CNN).

An image processing apparatus includes a detection unit that executes detection processing for detecting a particular object in an image, a holding unit that holds object information indicating a position and a size of the particular object on the image, a determination unit that determines whether a number of times a particular object is detected in the detection processing on one or more images reaches a predetermined value, a first setting unit that, when the number of times a particular object is detected in the detection processing on the one or more images is determined to reach the value, sets estimation areas on an image based on the object information obtained by the detection processing on the one or more images, and an estimation unit that executes estimation processing for estimating a number of the particular objects in the estimation areas.

The present application provides a hand tracking method, device and system, wherein the method comprises: determining a current frame image corresponding to each tracking camera respectively; acquiring tracking information of a hand location corresponding to the to-be-detected frame image and two-dimensional coordinates of a preset quantity of skeleton points according to the current frame images and the tracking information of the last frame image of the current frame images; determining three-dimensional coordinates of the preset quantity of skeleton points according to the two-dimensional coordinates and pre-acquired tracking data of a head location corresponding to the hand location; carrying out smoothing filter processing on the three-dimensional coordinates of the skeleton points and historical three-dimensional coordinates of the last frame image so as to acquire processed stable skeleton points; and fusing, rendering and displaying the stable skeleton points and the tracking data of the head location so as to complete tracking and display of the hand location.

A medical information display apparatus according to an embodiment includes processing circuitry. The processing circuitry is configured to display information on the basis of volume data including at least a lung. The processing circuitry is configured to display a first index value based on an anatomical structure of the lung and a second index value based on the volume data related to the lung, so as to be kept in correspondence with each other.

An object recognition processing apparatus includes: a model data acquisition unit configured to acquire three-dimensional model data of an object; a measurement unit configured to acquire measurement data including three-dimensional position information of the object; a position/orientation recognition unit configured to recognize a position/orientation of the object based on the three-dimensional model data and the measurement data; a similarity score calculation unit configured to calculate a similarity score indicating a degree of similarity between the three-dimensional model data and the measurement data in a position/orientation recognition result of the object; a reliability calculation unit configured to calculate an index indicating a feature of a three-dimensional shape of the object, and calculate a reliability of the similarity score based on the index; and an integrated score calculation unit configured to calculate an integrated score indicating a quality of the position/orientation recognition result based on the similarity score and the reliability.

A crop residue monitoring system may include a harvester, a camera to capture an image of crop residue generated by the harvester, an analytical unit to derive a value for a crop residue parameter of the crop residue based upon an optical analysis of the image and a control unit to adjust a subsequent field operation based upon the value of the crop residue parameter.

Systems and methods for detecting or following a person within an observed area. One example system includes a sensor and a processor configured to: receive, from the sensor, a series of readings indicative of the person in the observed area, wherein the observed area is divided into a plurality of zones; determine a sequential occurrence of each of a plurality of ordered events by applying a detection threshold value to the series of readings, wherein the detection threshold value is lower than a noise threshold of the sensor, and wherein each of the plurality of ordered events is associated with at least one of the plurality of zones; and determine a trigger condition based on the sequential occurrence of each of the plurality of ordered events; and provide an instruction to a fixture based on the trigger condition.

A chip recognition system in which a chip is configured to at least partially have a specific color indicative of a value of the chip includes: a recording device that uses a camera and records a state of the chip as an image; an image analysis device that subjects the image so recorded to image analysis and recognizes at least the specific color and a reference color that is present in the image and differs from the specific color; and a recognition device at least including an artificial intelligence device that uses a result of the image analysis by the image analysis device and specifies the specific color of the chip, wherein the artificial intelligence device of the recognition device has been subjected to teaching using, as training data, a plurality of images of the chip and the reference color irradiated with different illumination intensities.

A method for analysis of yeast includes: receiving a microscopic image of yeast by a cloud server (2901), the microscopic image including a scaling pattern for determining a magnification; determining the magnification by the cloud server based on the scaling pattern (2902); and analyzing, by the cloud server, the microscopic image based on the magnification to obtain an analysis result (2903).

A counting system 100 of the present invention includes an image acquisition means 121 for acquiring a captured image obtained by capturing an imaging area that is a partial area of an object area, a detection means 122 for detecting a person existing in the imaging area from the captured image, a measurement means 123 for, on the basis of a detection result of the person, measuring a staying time that is a period of time in which the person stays in the imaging area, and a calculation means 124 for, on the basis of the detection result of the person and the staying time, calculating the number of persons existing in the object area.