Abstract: A computer implemented method is disclosed herein for monitoring and determining a quality level of incoming raw material from one or more sources. The method includes (1) receiving visual data associated with the incoming raw material; (2) determining an indication of quality level associated with the incoming raw material; and (3) transmitting, to at least one of a graphical user interface (GUI) and a computer log, the indication of quality level and at least one timestamp associated with the visual data. The visual data may include a plurality of images received from one or more cameras configured for monitoring the incoming raw material. A related system is also disclosed herein.

Abstract: In an approach to non-destructive inspection of IC devices, one or more images of a Device Under Test (DUT) are received from one or more imaging devices. Observed features are detected in the one or more images and producing a first synthetic representation of a part design of the DUT that includes the observed features. The presence of one or more first unobserved features are inferred, where the one or more first unobserved features are inferred using a mapping and inference model (MIM). The one or more first unobserved features are added to the first synthetic representation of the part design of the DUT.

Abstract: A vehicle comprising a track system can be monitored to obtain information regarding the vehicle, including information regarding the track system, such as an indication of a physical state of a track and/or other component of the track system based on at least on 3D recognition and/or 2D recognition of image data of a track system component.

Abstract: A collision performance evaluation test with few variations in test results with high accuracy in which a complicated phenomenon that actually occurs can be reproduced in a simple manner by considering the history of deformation in both the press forming and a collision. A collision performance evaluation test method for a metal sheet material for an automobile body is characterized in that a press working apparatus first forms a flat test specimen made of a metal sheet material to be tested into a V shape by primary bending, a bending test apparatus then deforms, by secondary bending, the test specimen formed by the primary bending in a direction intersecting with the primary bending direction, and a bending load and a bending stroke for the test specimen during the secondary bending deformation are recorded and evaluated.

Abstract: An information processing device according to the present disclosure including: a mesh division unit (102) that divides at least part of first and second images captured at different times of a target area for detecting chips generated from a workpiece, into a plurality of mesh regions, the images each being an inside image of a machine tool; and an information processing unit (103) that performs processing to associate (a) information on a first chip corresponding to a specific mesh region among the plurality of the mesh regions corresponding to the first image, (b) information on a second chip corresponding to the specific mesh region among the plurality of the mesh regions corresponding to the second image, (c) a first time related to the first image, and (d) a second time related to the second image.

Abstract: A wafer defect detection apparatus and a method of fabricating an IC using the same. Images of a plurality of semiconductor wafers forming a wafer lot are captured at a targeted process step of a fabrication flow and preprocessed, wherein a medoid image is identified as a reference wafer image. In one arrangement, preprocessed wafer images of a semiconductor wafer lot may be analyzed for defects based on an ensemble of image analysis techniques using at least one of the reference wafer image from the wafer lot and a template patch to enhance the predictive power of defect detection.

Abstract: A system includes a robotic arm of a robotic device, an imaging device coupled to the robotic arm, and a processor configured to control movement of the robotic arm to move the imaging device along a preprogrammed measurement path of a transparency while prompting the imaging device to record images of localized portions of the transparency. The processor is configured to determine one or more localized transparency characteristics based on an analysis of the images of the localized portions.

Abstract: A display defect detection system and a detection method thereof are disclosed. A display defect detection system includes a preprocessing circuit receiving a capture image of a test pattern, displayed by a display panel, as a panel image including diagonal Mura and preprocessing the panel image to output a preprocessing image and a Mura detection circuit calculating a final feature value of the diagonal Mura by multiplying a first feature value, in which a luminance difference of the diagonal Mura is reflected, by a second feature value in which a shape ratio of the diagonal Mura is reflected, on the basis of an edge map of the preprocessing image, and detecting a display position of the diagonal Mura on the basis of the final feature value of the diagonal Mura.

Abstract: The present invention proposes a fabric defect detection method based on multi-modal deep learning. First, a tactile sensor is placed onto the fabric surface with different defects to collect the fabric texture images, a camera is used to collect the corresponding fabric external images, and a fabric external image and a fabric texture image constitute a set of fabric detection data; then, a feature extraction network and a multi-modal fusion network are connected to establish a classification model based on multi-modal deep learning, which uses the fabric texture image and fabric external image in each set of collected fabric detection data as input, and the fabric defect as output; said classification model is trained using the collected fabric detection data; finally, the trained classification model is used to detect the fabric defect. The present invention employs vision-touch complementary information, which can greatly improve the accuracy and robustness of detection.

Abstract: An image capturing unit captures an image of a surface of a member treated by a surface treatment unit. A comparison unit obtains a correlation coefficient between a reference image stored in a storage unit and the image captured by the image capturing unit. A cross-correlation coefficient between power spectra of the reference image and the image captured by the image capturing unit is obtained. A control unit stops a surface treatment performed by the surface treatment unit when the correlation coefficient obtained by the comparison unit reaches a set value.

Abstract: An inspection device is such that the inspection device executes a mounting inspection of a component using an inspection image of a board on which the component is mounted and includes an imaging device and an image processing device. The imaging device obtains three monochromatic images of the board in R, G, B. The image processing device sets a board color using brightness values of the three monochromatic images obtained by the imaging device, calculates complementary colors of the board color so set, determines on a color component having a largest brightness value in individual color components of the complementary colors so calculated, and sets the monochromatic image having the color component so determined in the obtained three monochromatic images as the inspection image.

Abstract: A method includes the steps collecting measurement data of a sample utilizing an adaptable inspection unit or while the sample is in-flight, determining a volume or area of the sample based at least in part on the measurement data, and calculating a weight of the sample based at least in part on the volume or area of the sample. The measurement data includes a captured image that includes a plurality of pixels. The determining of the volume of the sample includes determining the number of pixels in the captured image that display a portion of the sample, or determining the maximum number of consecutive pixels that display a portion of the sample in two or three dimensions.

Abstract: An example embodiment of the present invention provides a method of assessing the condition of a pavement site, comprising: (a) acquiring aerial images of the site from above, for example by an unmanned aerial system (UAS); (b) using photogrammetry tools to generate an orthomosaic that represents the airport pavement surface; (c) using image analysis tools and machine learning methods to determine the location and extent of defects in the pavement; (c) producing an image representation of the site and the defects, where the location and extent of defects are discernible from the image; (d) using software application techniques to store and present defect data and other related information for client-side user access.

Abstract: The present disclosure includes edge defect detection via image analytics. A method includes identifying an image of an edge of a susceptor pocket formed by a susceptor of a substrate processing system. The method further includes predicting, based on the image, whether property values of the edge of the susceptor meet threshold values. The method further includes, responsive to the property values of the edge meeting threshold values, causing performance of a corrective action associated with the susceptor.

Abstract: A method for specifying a position through touch input in a screen displayed on a touch panel display. The position is specified by acquiring an initial contact position with the touch panel display, displaying a position displaying cursor in a position according to the initial contact position, displaying the position displaying cursor in the position according to the initial contact position during the period for which the contact position sensing continues until the distance from the initial contact position to the contact position reaches a predetermined distance and terminating the display of the position displaying cursor where the contact position sensing is terminated before the distance reaches the predetermined distance, and displaying the position displaying cursor in such a way that the position displaying cursor follows movement of the contact position after the distance reaches the predetermined distance.

Abstract: One variation of a method for predicting manufacturing defects includes: accessing a first set of inspection images of a first set of assembly units recorded by an optical inspection station over a first period of time; generating a first set of vectors representing features extracted from the first set of inspection images; grouping neighboring vectors in a multi-dimensional feature space into a set of vector groups; accessing a second inspection image of a second assembly recorded by the optical inspection station at a second time succeeding the first period of time; detecting a second set of features in the second inspection image; generating a second vector representing the second set of features in the multi-dimensional feature space; and, in response to the second vector deviating from the set of vector groups by more than a threshold difference, flagging the second assembly unit.

Abstract: A method for detecting a display panel defect, including: collecting a panel image of a to-be-detected display panel, a plurality of first pixels of the display panel corresponding to a plurality of second pixels in the panel image; converting the panel image into a binary image; dilating each bright spot region in the binary image such that adjacent bright spot regions communicate with each other to form at least one closed communication region in the binary image; determining a region of interest mask image in the binary image in accordance with the at least one closed communication region; determining a region of interest in accordance with the region of interest mask image and the panel image; and performing feature identification on the region of interest to determine a defect of the display panel.

Abstract: A system and method are provided for super-resolution imaging beyond the Rayleigh spatial resolution limit of an optical system. In the context of a system, first and second pinhole assemblies are configured to be controllably positioned. The first and second pinhole assemblies define respective pinholes and being configured to be backlit. The system also includes a collimating lens configured to collimate at least a portion of the signals passing through the respective pinholes of the first and second pinhole assemblies. The system further includes an amplitude/phase mask configured to provide amplitude and phase modulation to signals received from the collimating lens and an imaging lens configured to focus the signals received from the amplitude/phase mask upon an image plane to permit objects to be separately identified.

Abstract: An imaging system is for recording images of a raceway of a bearing ring, the ring having two opposing axial ends, a central axis extending between the axial ends, and inner and outer circumferential surfaces. The raceway is formed on the inner circumferential surface or the outer circumferential surface of the ring and has first and second ends spaced along the central axis. The imaging system includes a frame movably coupleable with the bearing ring and having a centerline. A drive is mounted to the frame and is configured to angularly displace the frame about the bearing central axis. An optical imager has a lens and an adjustable positioner is mounted on the frame and is configured to position the optical imager such that the lens is disposed axially between the raceway first and second ends and faces generally perpendicular to the bearing raceway.

Abstract: An apparatus for forming and applying artificial fingernails is disclosed herein. In one or more embodiments, the apparatus includes a housing; a rotatable carousel disposed at least partially within the housing, the rotatable carousel including a plurality of fingernail molds that are configured to be rotated with the carousel, the plurality of fingernail molds configured to form a plurality of different fingernail shapes using an artificial fingernail molding material; a dispensing device disposed at least partially within the housing, the dispensing device configured to dispense the artificial fingernail molding material onto a fingertip portion of a user within a selected one of the plurality of fingernail molds; and a curing device, the curing device configured to cure the artificial fingernail molding material on the fingertip portion of the user so as to form an artificial fingernail having a particular shape.

Abstract: Systems and methods are provided for automating property assessment using probable roof loss confidence scores. More particularly, the systems and methods may generate a base-line probable roof loss confidence score based upon buildings, roof, weather, hail, and climate data. The systems and methods may predict a specific event and a set of characteristics of the specific event. The systems and methods may predict a level of roof damage and a cost of roof damage based upon the predicted level of roof damage. The systems and methods may adjust a risk-related factor, and may further adjust policy parameters based upon the risk-related factor. A probable roof loss confidence score may be generated, as well as property insurance claims data or property insurance loss mitigation data based upon probable roof loss confidence score data.

Abstract: An individual identification apparatus includes a setting means for setting an imaging condition for imaging a matching area of an object by a camera, an acquisition means for acquiring a matching image that is an image obtained by imaging the matching area of the object by the camera, a matching means for performing matching between the matching image and a registration image registered in advance, and a control means. The control means repeats processing of acquiring the matching image by the acquisition means and matching between the matching image and the registration image by the matching means, while changing the imaging condition set by the setting means, and determines an imaging condition in which a matching degree between the matching image and the registration image becomes a preset threshold or larger. The matching means identifies an individual based on the matching image captured under the determined imaging condition.

Abstract: A computer system is provided for converting images through use of a trained neural network. A source image is divided into blocks and context data is added to each pixel block. The context blocks are split into channels and each channel from the same context block is added to the same activation matrix. The action matrix is then executed against a trained neural network to produce a changed activation matrix. The changed activation matrix is then used to generate a converted image.

Abstract: The present application discloses a method and device for controlling misalignment of electrode plates, electrode plates, an electrochemical cell, and a battery. The method includes: acquiring cut hole position information of an anode electrode plate, and calculating a first width deviation value corresponding to the anode electrode plate according to the cut hole position information and a calibration width of the anode electrode plate; acquiring tab position information of a cathode electrode plate, and calculating a second width deviation value corresponding to the cathode electrode plate according to the tab position information and a calibration width of the cathode electrode plate; and when the anode electrode plate and the cathode electrode plate are stacked, adjusting a feed position of the cathode electrode plate according to the first width deviation value, and compensating for a cut width of the cathode electrode plate according to the second width deviation value.

Abstract: A system and method for image series transformation for optimal compressibility with neural upsampling. It incorporates a novel AI deblocking network composed of convolutional layers for feature extraction and a channel-wise transformer with attention to capture complex inter-channel dependencies. Additionally, the system includes an angle optimizer to further enhance the compressibility of an image. The convolutional layers extract multi-dimensional features from the image, while the channel-wise transformer learns global inter-channel relationships. This hybrid approach addresses both local and global features, mitigating compression artifacts and improving image quality. The model's outputs enable effective image reconstruction, achieving advanced compression while preserving crucial information for accurate analysis.

Abstract: An image defect detection method applied to an electronic device is provided. The method includes dividing a detecting image into a plurality of detecting areas, generating a detection accuracy value for each detecting area based on a defective image and a non-defective image, and obtaining a plurality of detection accuracy values. An autoencoder is selected for each detection accuracy value. A model corresponding to each detecting area is obtained by training the autoencoder based on the non-defective image. A plurality of reconstructed image blocks is obtained by inputting each of a plurality of detecting blocks into the corresponding model, and a reconstruction error value between each reconstructed image block and the corresponding detecting block is obtained. A detection result of a product contained in the image to be detected is obtained based on the reconstruction error value corresponding to each detecting block.

Abstract: An inspection system is provided and includes a camera and controller. The controller can include one or more processors in communication with the camera and receive a plurality of images of a target captured by the camera. The controller can also determine, using a first computer vision algorithm, a first prediction and corresponding confidence level for substantially all of the images. The controller can select a subset of the images having the first prediction confidence level greater than or equal to a first prediction threshold value. The controller can additionally determine, using a second computer vision algorithm, a second prediction and corresponding second prediction confidence level for each of the selected images. The at least one second prediction can require more time to determine than the at least one first prediction. The controller can output the second prediction and the second prediction confidence level for each of the selected images.

Abstract: An inspection system is provided and includes a camera and controller. The camera can acquire at least one image of a target including opposed first and second surfaces. The controller can be in communication with the camera and receive the at least one image. The controller can also detect, using at least one computer vision algorithm, a geometry of the target including the first target surface and the second target surface of the target within at least one image. The at least one image can be acquired at a respective time under respective operating conditions. The controller can additionally segment erosion within the at least one image using the at least one computer vision algorithm. The controller can also generate an erosion depth profile for the at least one image. The erosion depth profile can characterize a depth of erosion of the target between the first and second surfaces.

Abstract: This invention provides a system and method for finding patterns in images that incorporates neural net classifiers. A pattern finding tool is coupled with a classifier that can be run before or after the tool to have labeled pattern results with sub-pixel accuracy. In the case of a pattern finding tool that can detect multiple templates, its performance is improved when a neural net classifier informs the pattern finding tool to work only on a subset of the originally trained templates. Similarly, in the case of a pattern finding tool that initially detects a pattern, a neural network classifier can then determine whether it has found the correct pattern. The neural network can also reconstruct/clean-up an imaged shape, and/or to eliminate pixels less relevant to the shape of interest, therefore reducing the search time, as well significantly increasing the chance of lock on the correct shapes.

Abstract: In an embodiment a method includes placing a wafer on a receptacle comprising a chuck base, wherein a light port for emitting light from a source of light is an opening located in a surface of the chuck base, and wherein the light port is located underneath the wafer, shining the light from the light port at an edge of the wafer so that light passes by the edge of the wafer and processing the wafer on the receptacle based on the light that passed by the edge of the wafer and that is received by a light sensitive element.

Abstract: A processor determines an image defect in a test image obtained through an image reading process performed on an output sheet output by an image forming apparatus. The processor creates an image to be processed including a horizontal line, extending in a horizontal direction, extracted from the test image. Furthermore, the processor determines the presence or absence of at least one periodicity set in advance in a vertical direction in the image to be processed and determines the cause of the horizontal line according to the determination result on the periodicity.

Abstract: Embodiments described herein provide for a defect detection system and method suitable for detecting defects on an edge of a wafer. The method includes placing at least two wafers sequentially on a conveyor. Images of at least the edges of each wafer placed on the conveyor are captured and sent to a controller. A defect detection software combines the images to show the edges of the wafers in a virtual stack. The virtual stack allows for a pattern of defects to be identified. The pattern of defects in close proximity will allow for identification of the defects in the edges of the wafers.

Abstract: A method of manufacturing a display includes coupling light from at least one light source into a front illumination film-based lightguide comprising a pressure sensitive adhesive layer between a core polymer film layer and a diffusely reflective release liner such that light from the at least one light source propagates by total internal reflection through the core polymer film layer, is extracted from the core polymer film layer, passes through the pressure sensitive adhesive layer, diffusely reflects from the diffusely reflective release liner and passes back through the pressure sensitive adhesive layer and core polymer film layer out of the front illumination film-based lightguide; analyzing the light exiting front illumination film-based lightguide from the at least one light source for defects; removing the diffusely reflective release liner from the front illumination film-based lightguide after analyzing; and laminating the front illumination film-based lightguide to a reflective spatial light modula

Abstract: The present disclosure relates to a system and method for detecting an address block and barcode on a captured image of an item, and reading the detected barcode using connected component analysis. In one aspect, the method includes binarizing a captured image to generate a binarized image having pixel values, inverting the pixel values of the binarized image, processing the inverted pixel values, and filtering the processed image by area. The method may also include machine learning the processed image to cluster objects in the processed image into a plurality of groups using the filtered image, and determining a number of objects in each of the clustered groups by performing additional operations on the clustered objects to detect the address block. The method may also include selecting the group having the greatest number of objects as the address block, and extracting the selected address block.

Abstract: Various examples include a system and network to map of substrates within a substrate carrier (e.g., such as silicon wafers within a wafer cassette), and a classification of a state of each substrate, as well as the carrier in which the substrates are placed. In various examples provided herein, an image acquisition system, such as a camera, acquires multiple images of the substrates within the carrier. The image or images are then processed with a deep-convolutional neural-network to classify a state of the substrate relative to a substrate slot including empty slots, occupied slots (e.g., properly loaded slots), double-loaded slots, cross-slotted, and protruded (where a substrate is not fully loaded into a slot).

Abstract: An inspection device includes a processor configured to acquire image information of each of a correct image and a target image as an inspection target, extract edge information of each of the correct image and the target image by using the acquired image information, obtain a difference image between the correct image and the target image, and change a threshold value for detecting a defect by using brightness information or color information of the correct image along with the edge information and detect a defect of the target image by using the difference image and the threshold value.

Abstract: An example three-dimensional (3D) printer may include a camera to capture a low-resolution thermal image of a build material bed. The 3D printer may include an interpolation engine to generate an interpolated thermal image based on the low-resolution thermal image. The 3D printer may also include a correction engine to enhance fine details of the interpolated thermal image without distorting thermal values from portions of the interpolated thermal image without fine details to produce an enhanced thermal image.

Abstract: The present disclosure generally relates techniques for audio-assisted enrollment of biometric features. In some embodiments, methods and devices for assisting users with enrollment of biometric features, using spatial audio cues, are described.

Abstract: An image inspection device includes: an inspection condition setting unit for setting, as an inspection condition, a determination criterion when detecting a defective image; an imaging unit that performs capturing a print image and outputs a captured image obtained by the capturing; and a defective image detection unit that detects a defective image from the captured image on the basis of the inspection condition. The inspection condition setting unit is configured to be able to set, as the inspection condition, first parameter values and second parameter values that are two different determination criteria. The defective image detection unit performs first detection processing of detecting a defective image from the captured image on the basis of the first parameter values and second detection processing of detecting a defective image from the captured image on the basis of the second parameter values.

Abstract: A model input size determination method, an electronic device and a storage medium are provided, the method includes acquiring a plurality of test images and a defect result; and encoding each test image to obtain an encoding vector. The encoding vector is decoded to obtain a reconstructed image, then a reconstruction error and a plurality of sub-vectors are calculated; the plurality of sub-vectors is inputted into a Gaussian mixture model, then a plurality of sub-probabilities, an estimated probability and a test error are determined; a detection result in the test image according to the test error and the corresponding error threshold are obtained; an accuracy according to the detection result and the defect result are determined, and an input size is selected from the plurality of preset sizes according to the accuracy. An accuracy of defect detection in manufacturing can be improved.

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: An information processing device processes image data representing a distribution of at least one numerical data in a specific space. The information processing device includes a storage unit and an inference unit. The storage unit stores an image recognition program. The inference unit extracts specific information about the at least one numerical data from the image data by executing the image recognition program. A symbol having an appearance corresponding to each of the at least one numerical data is disposed at a position associated with the numerical data in the specific space.

Abstract: An information processing apparatus includes a control unit that controls a first flying vehicle and a second flying vehicle. The first flying vehicle captures an image of a surface of a road. The second flying vehicle emits light onto the surface, such that a spot where a level difference is estimated, in advance, to occur on the surface, an image capturing direction in which the first flying vehicle captures an image of the spot, and a light emitting direction in which the second flying vehicle emits the light onto the spot have a relationship that causes, when the level difference exists, a shadow to occur at the spot and the shadow to be captured.

Abstract: A method includes the steps collecting measurement data of a sample utilizing an adaptable inspection unit or while the sample is in-flight, determining a volume or area of the sample based at least in part on the measurement data, and calculating a weight of the sample based at least in part on the volume or area of the sample. The measurement data includes a captured image that includes a plurality of pixels. The determining of the volume of the sample includes determining the number of pixels in the captured image that display a portion of the sample, or determining the maximum number of consecutive pixels that display a portion of the sample in two or three dimensions.

Abstract: Described herein is a computer-implemented process which includes at least the following steps: receiving at least one image or a plurality of images, implementing an image analysis for each of the images obtained, using at least one processor, identifying at least one sparkle point within a respective image, implementing a features analysis of the at least one identified sparkle point in the respective image in respect of at least one predefined size feature, determining at least one value for the at least one predefined size feature for the at least one sparkle point, calculating a size distribution for the respective image based on the determined value for the at least one predefined size feature, and providing a formulation for a coating which is identical or at least similar in appearance to the target coating.

Abstract: A system for capturing a product tag image, extracting product information, and validating information. The extracted information is then utilized to populate a universal (brand independent) product registration database. To incentivize end users to register their new and in service products, entry is simplified by the use of an application on a smartphone, tablet or personal computer. A user downloads an application and enters their information then takes at least one picture/scan/image of the product label(s) that contain: 1) manufacturer name (and/or brand name), 2) model number, 3) serial number; and 4) date of production. Said information is extracted by Optical Character Recognition (OCR) and then validated before entering said database.

Abstract: An exemplary system and method are disclosed for detecting malware via an antimalware application employing adversarial machine learning such as generative adversarial machine learning and the training and/or configuring of such systems. The exemplary system and method are configured with two or more generative adversarial networks (GANs), including (i) a first generative adversarial network (GAN) that can be configured using a library of malware code or non-malware code and (ii) a second generative adversarial network (GAN) that operates in conjunction with the first generative adversarial network (GAN) in which the second generative adversarial network is configured using a library of non-malware code.

Abstract: Systems and methods for inspecting the outer skin of a honeycomb body are provided. The inspection system comprises a rotational sub-assembly configured to rotate the honeycomb body, a camera sub-assembly configured to image at least a portion of the outer skin of the honeycomb body as it rotates, a three-dimensional (3D) line sensor sub-assembly configured to obtain height information from the outer skin of the honeycomb body; and an edge sensor sub-assembly configured to obtain edge data from the circumferential edges of the honeycomb body. In some examples, the inspection system utilizes a universal coordinate system to synchronize or align the data obtain from each of these sources to prevent redundant or duplicative detection of one or more defects on the outer skin of the honeycomb body.

Abstract: Embodiments of the present application provide a detection method, a detection device, and a storage medium. The detection method may comprise: obtaining a to-be-detected image; obtaining a plurality of confidence levels corresponding to a plurality of detection items according to the to-be-detected image; and determining a detection result of the to-be-detected image according to the plurality of confidence levels and a plurality of detection thresholds, where the plurality of detection thresholds may be corresponding to the plurality of detection items and may be a non-inferior solution of objective functions of an overkill rate and a missed detection rate, the overkill rate may be the ratio of qualified ones detected as defective, and the missed detection rate may be the ratio of defective ones detected as qualified.

Abstract: An exemplary system and method are disclosed for detecting malware via an antimalware application employing adversarial machine learning such as generative adversarial machine learning and the training and/or configuring of such systems. The exemplary system and method are configured with two or more generative adversarial networks (GANs), including (i) a first generative adversarial network (GAN) that can be configured using a library of malware code or non-malware code and (ii) a second generative adversarial network (GAN) that operates in conjunction with the first generative adversarial network (GAN) in which the second generative adversarial network is configured using a library of non-malware code.