Abstract: The present disclosure describes a method of foreground segmentation and nucleus ranking for scoring dual ISH images. The method has been developed to better identify those nuclei, within a selected field of view, that meet the criteria for dual ISH scoring.

Abstract: Examples of the disclosure provide an apparatus for authentication of images. The apparatus comprises means for: receiving one or more images captured by an imaging device; extracting one or more light patterns from the one or more images where the one or more light patterns correspond to light reflected from at least part of an object that was positioned out of field of view of the imaging device when the one or more images were captured so that the at least part the object does not appear in the one or more images but light reflected from the at least part of the object that was positioned out of field of view creates the one or more light patterns in the one or more images; and determining if the extracted one or more light patterns correspond to a predetermined object to enable authentication of the one or more images.

Abstract: A method of analyzing film on a substrate comprises receiving surface profile data obtained from measurements of a substrate having a plurality of discrete regions with one or more film layers; extracting, based on a predetermined pattern of the discrete regions, a plurality of parameters from the received surface profile data, the plurality of parameters comprising one or more parameters of a film layer of each discrete regions, and displaying a user interface. The user interface may comprise a plurality of individual graphs each illustrating the one or more parameters of the one or more film layers for a corresponding subset of the plurality of discrete regions, and a composite graph illustrating the one or more parameters of the one or more film layers for each discrete region of the plurality of discrete regions, wherein the composite graph corresponds to the plurality of individual graphs being overlaid together.

Abstract: An image processing apparatus that can determine reliability of rounding processing on numerical values obtained by character recognition processing. The image processing apparatus performs character recognition of a plurality of numerical values from image data, acquires a learning result indicating a rounding processing method from a storage unit that stores the learning result, and determines reliability of the character recognition on the basis of a difference between a calculation result of the plurality of numerical values and a calculation result of the plurality of numerical values in a case where the rounding processing indicated by the acquired learning result is applied.

Abstract: Video feeds may be analyzed to identify matchups between participants. The matchups may be used to derive a competition, context, statistics, and the like. A result of the derived competition may depend, at least in part, on an ordering and outcomes of a set of matchup events. The derived competition may be presented as a collection of video clips corresponding to the set of matchup events, related commentary, and/or related statistics.

Abstract: An automated vehicle parking system for a motor vehicle is disclosed and includes at least one camera obtaining images proximate a vehicle, at least one sensor array detecting objects proximate the vehicle, and a controller configured to generate a mask of an area proximate the vehicle from the images obtained by the at least one camera including labeled features identified within the obtained images and project the generated mask onto an occupancy grid generated with information from the at least one sensor array, wherein the controller is configured to locate a parking space responsive to open spaces defined within the generated mask.

Abstract: Two models are first trained and then test images are applied to the two trained models in an effort to detect signature forgeries. The first model is trained with pairs of signature images and the resultant trained model is capable of detecting blind forgeries. The second model is trained with triplets of signature images and is capable of detecting skilled signature forgeries. After the two models are trained, test images are applied to the models and determinations are made as to whether a blind or skilled forgery is present.

Abstract: A method and system are disclosed for monitoring passengers in within a cabin of a vehicle and determining whether the passengers are engaging in abnormal behavior. The method and system uses a novel vector to robustly and numerically represent the activity of the passengers in a respective frame, which is referred to herein as an “activity vector.” Additionally, a Gaussian Mixture Model is utilized by the method and system to distinguish between normal and abnormal passenger behavior. Cluster components of the Gaussian Mixture Model are advantageously learned using an unsupervised approach in which training data is not labeled or annotated to indicate normal and abnormal passenger behavior. In this way, the Gaussian Mixture Model can be trained at a very low cost.

Abstract: Methods and systems are described herein for hosting and arbitrating algorithms for the generation of structured frames of data from one or more sources of unstructured input frames. A plurality of frames may be received from a recording device and a plurality of object types to be recognized in the plurality of frames may be determined. A determination may be made of multiple machine learning models for recognizing the object types. The frames may be sequentially input into the machine learning models to obtain a plurality of sets of objects from the plurality of machine learning models and object indicators may be received from those machine learning models. A set of composite frames with the plurality of indicators corresponding to the plurality of objects may be generated, and an output stream may be generated including the set of composite frames to be played back in chronological order.

Abstract: Methods, systems, devices, and tangible non-transitory computer readable media for generating assistive indications are provided. The disclosed technology can include accessing image data that includes at least one image. Character data can be generated based at least in part on the image data and one or more optical character recognition operations. Further, the character data can include one or more characters associated with the at least one image. One or more characters that are associated with one or more recognized words and the one or more characters that are associated with one or more unrecognized words can be determined based on the character data. One or more auditory indications including a synthetic voice reciting the one or more recognized words and the one or more unrecognized words can be generated. Furthermore, the synthetic voice can recite each of the one or more unrecognized words one character at a time.

Abstract: An electronic apparatus and a controlling method thereof are provided. The controlling method according to an embodiment includes acquiring contents and storing the contents in a memory, identifying a first section of the contents related to a first behavior by analyzing the stored contents, outputting contents of the identified first section, acquiring a user image captured while the contents of the first section is output, identifying whether the first behavior is completed by analyzing the user image, and based on identifying that the user has completed the first behavior, outputting contents of a second section, the second section being a next section of the first section.

Abstract: This disclosure relates to managing a feature point map. The managing can include adding feature points to the feature point map using feature points captured by multiple devices and/or by a single device at different times. The resulting feature point map may be referred to as a global feature point map, storing feature points from multiple feature point maps. The global feature point map may be stored in a global feature point database accessible by a server so that the server may provide the global feature point map to devices requesting feature point maps for particular locations. In such examples, the global feature point map may allow a user to localize in locations without having to scan for feature points in the locations. In this manner, the user can localize in locations in which the user has never previously visited.

Abstract: A lane line recognition apparatus includes an imaging device, a lane-line-search-region setting section, a light-streak-search-region setting section, a light-streak determination section, a light-streak-reaching determination section, and a mask processing section. The imaging device is to be mounted on a vehicle and captures an image of a traveling environment in front of the vehicle. The lane-line-search-region setting section sets a lane-line search region on the image. The light-streak-search-region setting section sets a light-streak search region adjacently to the lane-line search region. The light-streak determination section determines whether a light streak that crosses, in a vertical direction of the image, the light-streak search region is found. The light-streak-reaching determination section determines, if the light streak is found, whether the light streak reaches the lane-line search region.

Abstract: Disclosed are a system and methods for operating an autonomous or semi-autonomous vehicle. One method comprises travelling in an outdoor setting, capturing data related to the outdoor setting, processing captured data and identifying occlusion present in the preprocessed data. The system comprises an autonomous or semi-autonomous vehicle configured to travel in outdoor settings and comprising at least one first sensor and at least one processing component. The processing component is configured to process data captured by the first sensor and identify occlusion present in the preprocessed data.

Abstract: Generating a training image for use in training a region-of-interest detector that is trained to detect regions-of-interest within images includes generating a closed geometric shape; filling the closed geometric shape with a filler to obtain a blob; overlaying the blob on an edge of an image to obtain the training image, where the image includes a region-of-interest and a background region, and where the edge separates the region-of-interest from the background region; and using the training image to train the region-of-interest detector to detect a boundary of the region-of-interest. An input to the region-of-interest detector in a training phase includes the training image and a first indication of coordinates of the region-of-interest in the training image. An output of the region-of-interest detector includes a second indication of an area of the training image and a probability of the area of the training image being the region-of-interest.

Abstract: An approach is provided for confirming road vector geometry based on aerial image(s). For example, the approach involves retrieving a feature and a vector representation of a road link. The approach also involves processing one or more aerial images depicting the road link to extract a list of spectral pixel values corresponding to the vector representation. The approach further involves determining a degree of misalignment between the spectral pixel values and a spectral signature of the feature of the road link. The approach further involves initiating a confirmation of a geometry of the vector representation based on the degree of misalignment. The approach further involves providing the confirmation as an output.

Abstract: A backlight face recognition method, a terminal device using the same, and a computer readable storage medium are provided. The method includes: performing a face detection on each original face image in an original face image sample set to obtain a face frame corresponding to the original face image; capturing the corresponding original face images from the original face image sample set, and obtaining a new face image containing background pixels corresponding to the captured original face images from the original face image sample set; preprocessing all the obtained new face images to obtain a backlight sample set and a normal lighting sample set; and training a convolutional neural network using the backlight sample set and the normal lighting sample set until the convolutional neural network reaches a preset stopping condition. The trained convolutional neural network will improve the accuracy of face recognition in complex background and strong light.

Abstract: An example apparatus for semantic image segmentation includes a receiver to receive an image to be segmented. The apparatus also includes a gated dense pyramid network including a plurality of gated dense pyramid (GDP) blocks to be trained to generate semantic labels for respective pixels in the received image. The apparatus further includes a generator to generate a segmented image based on the generated semantic labels.

Abstract: A system for detecting an object collision includes a processor and a memory in communication with the processor with an objection collision detection module. The objection collision detection module has instructions that, when executed by the processor, cause the processor to obtain a first image and a second image of a scene from a camera sensor mounted to a vehicle, determine a change amount between the first image and the second image, and based on the change amount, determine at least one of that an object is approaching the vehicle or the object has collided with the vehicle. The change amount represents the number of pixels with the same location value that changed intensity values between the first and second images.

Abstract: Systems and methods are described for the compositing together of model-linked vascular data from a plurality of sources, including at least one 2-D angiography image, for display in a frame of reference of the at least one angiography image. In some embodiments, a linking model comprises a data structure configured to link locations of angiographic images to corresponding elements of non-image vascular parameter data. The linking data structure is traversed to obtain a mapping to the frame of reference of one or more of the angiographic images.