A defect inspection device is provided with an illumination optical system that irradiates light or an electron beam onto a sample, a detector that detects a signal obtained from the sample through the irradiation of the light or electron beam, a defect detection unit that detects a defect candidate on the sample through the comparison of a signal output by the detector and a prescribed threshold, and a display unit that displays a setting screen for setting the threshold. The setting screen is a two-dimensional distribution map that represents the distribution of the defect candidates in a three dimensional feature space having three features as the axes thereof and includes the axes of the three features and the threshold, which is represented in one dimension.

An electronic apparatus including a display and one or more processor is disclosed. The one or more processor is configured to: divide a first error value of each of a plurality of first components with respect to a mounting position acquired through inspection of a plurality of substrates of a first type, into a plurality of error values, generate a graph of a tree structure including a plurality of nodes corresponding to the plurality of first components, component types of each of the plurality of first components and a plurality of components included in a mounter, adjust attributes of each of the plurality of nodes using the plurality of error values divided from the first error value of each of the plurality of first components, and display the graph in which the attributes of each of the plurality of nodes are adjusted, on the display.

An electronic apparatus including a display and one or more processor is disclosed. The one or more processor is configured to: divide a first error value of each of a plurality of first components with respect to a mounting position acquired through inspection of a plurality of substrates of a first type, into a plurality of error values, generate a graph of a tree structure including a plurality of nodes corresponding to the plurality of first components, component types of each of the plurality of first components and a plurality of components included in a mounter, adjust attributes of each of the plurality of nodes using the plurality of error values divided from the first error value of each of the plurality of first components, and display the graph in which the attributes of each of the plurality of nodes are adjusted, on the display.

There is presented a system and method for detecting mobile device fault conditions, including detecting fault conditions by software operating on the mobile device. In one embodiment, the present invention provides for systems and methods for using a neural network to detect, from an image of the device, that the mobile device has a defect, for instance a cracked or scratched screen. Systems and methods also provide for, reporting the defect status of the device, working or not, so that appropriate action may be taken by a third party.

Disclosed is a method for estimating twin defect density in a single-crystal sample, including: (A) etching the observed surface of a single crystal to form etch pits; (B) selecting bar-shaped etch pits caused by twin defect; (C) from the long-axis direction lengths of the etch pits caused by twin defect, estimating the twin defect density by using the following equation: twin defect density=Σkx′.sub.i/area of sample, wherein 2≤k≤3, and x′.sub.i is the long-axis direction length of an etch pit caused by the i-th twin.

Methods of performing metrology. In one arrangement a substrate has a layer. The layer comprises a two-dimensional material. A target portion of the layer is illuminated with a beam of radiation and a distribution of radiation in a pupil plane is detected to obtain measurement data. The measurement data is processed to obtain metrology information about the target portion of the layer. The illuminating, detecting and processing are performed for plural different target portions of the layer to obtain metrology information for the plural target portions of the layer.

Enhanced evaluation of pre-owned electronic devices related services are described. Example evaluation devices (e.g. kiosks etc.) and techniques for enhanced evaluation are described. An example evaluation device includes an evaluation area in which a previously-owned electronic device (e.g. smartphone etc.) is arranged with its camera configured to capture images of the evaluation area. An example apparatus includes a previously-owned electronic device arranged with its camera configured to capture images of another previously-owned electronic device within an evaluation area. Other example implementations include detecting microdefects and/or micro-differences for identifying a device; based on an evaluation of a device, providing any of a repair quote, an insurance or warranty quote, an insurance or warranty claim, a certification, or a promise to purchase; processing evaluation session attributes based on the selected context; and providing a point-of-sale integration component configured to intercept data from a coupon reader.

An information processing apparatus includes a reception unit configured to receive an input specifying a position of a detection target included in an image, an acquisition unit configured to acquire a storage amount of training data including a pair of information indicating the image and information indicating the position specified by the input, a training unit configured to train a training model to detect the detection target from the image based on the stored training data, and a display control unit configured to control a display unit to display the storage amount, and a reference amount of the training data set as an amount of the training data necessary for the training unit to train the training model, in a comparable way.

Disclosed is a method for estimating twin defect density in a single-crystal sample, including: (A) etching the observed surface of a single crystal to form etch pits; (B) selecting bar-shaped etch pits caused by twin defect; (C) from the long-axis direction lengths of the etch pits caused by twin defect, estimating the twin defect density by using the following equation: twin defect density=Σkx′.sub.i/area of sample, wherein 2≤k≤3, and x′.sub.i is the long-axis direction length of an etch pit caused by the i-th twin.

A measurement device includes: an obtainer that obtains a plurality of images of a support member that movably supports a structure, the plurality of images being captured at mutually different times while the structure is subjected to varying loads; and a measurer that measures displacement of the support member based on the plurality of images obtained by the obtainer.