Abstract: A result format modifying method, system, and non-transitory computer readable medium, include extracting, from a database including a plurality of display format types of a search result of a search conducted by a user, the plurality of display format types of the search result conducted by the user, and deciding a display format of the plurality of display format types to output to the user based on a time interval between a current time and the start time of the user's next activity as determined by the determining, where the display format of the search result to the user corresponds to a delivery that is digestible by the user within a specific length of a time interval out of a first time interval and a second time interval, the first time interval being longer than the second time interval.

Abstract: At a sending electronic device, from a remote location, an indication is received of an environment at a receiving mobile electronic device to which the sending electronic device is to send a message. It is determined how to send the message from the sending electronic device to the receiving mobile electronic device, based on the indication of the environment at the receiving mobile electronic device. The message is sent from the sending electronic device to the receiving mobile electronic device in accordance with the determining step.

Abstract: At a sending electronic device, from a remote location, an indication is received of an environment at a receiving mobile electronic device to which the sending electronic device is to send a message. It is determined how to send the message from the sending electronic device to the receiving mobile electronic device, based on the indication of the environment at the receiving mobile electronic device. The message is sent from the sending electronic device to the receiving mobile electronic device in accordance with the determining step.

Abstract: A computer-implemented screening method, system, and computer program product including processing a first sensor scan image at a first time and at a first location to detect a first disassembled component of an object, processing a second sensor scan image at a second time and at a second location to detect a second disassembled component of the object, storing a record of the first disassembled component and the second disassembled component, and flagging the record based on a risk factor of the first disassembled component being combined with the second disassembled component to complete the object.

Abstract: A computer-implemented screening method, system, and computer program product including detecting at least two disassembled components of an object spread across multiple sensor scan images of at least one container, storing a record of each disassembled component correlated with contextual information of each owner of each container corresponding to a sensor scan image, and flagging the owner of the container in the sensor scan image based on a joint assessment of the sensor scan image including a disassembled component that can be combined with another disassembled component in a different sensor scan image to assemble the object and the contextual information of each owner.

Abstract: Systems and techniques for providing an artificial intelligence based annotation framework with active learning for image analytics are presented. In one example, a system annotates training data associated with a set of images for a feature learning process. The system also incrementally updates an analytics artificial intelligence model for an engineering component based on the feature learning process.

Abstract: Described herein, system that facilitates OCR error correction based on visual and textual contents. According to an embodiment, a system can comprise splitting a scanned content into blocks using a neural network and tags the blocks as textual content and image content. The system can further comprise converting, the textual content to a word feature vector. The system can further comprise converting the image content to an image feature vector.

Abstract: Solar irradiation may be predicted based on input terrestrial sky images comprising cloud images, the terrestrial sky images taken from a plurality of geographic locations by a plurality of devices; for example, wherein the terrestrial sky images are crowd sourced from the plurality of devices. A model may be generated that predicts solar irradiation in a geographic area based on the input terrestrial sky images and the geographic locations from where the terrestrial sky images were taken. A signal representing the solar irradiation predicted by the model is output.

Abstract: A method for image analysis comprises receiving one or more images of a plurality of lesions captured from a body of a person, extracting one or more features of the plurality of lesions from the one or more images, analyzing the extracted one or more features, wherein the analyzing comprises determining a distance between at least two lesions with respect to the extracted one or more features, and determining whether any of the plurality of lesions is an outlier based on the analyzing.

Abstract: A result format modifying method, system, and non-transitory computer readable medium, include extracting, from a database including a plurality of display format types of a search result of a search conducted by a user, the plurality of display format types of the search result conducted by the user, and deciding a display format of the plurality of display format types to output to the user based on a time interval between a current time and the start time of the user's next activity as determined by the determining, where the display format of the search result to the user corresponds to a delivery that is digestible by the user within a specific length of a time interval out of a first time interval and a second time interval, the first time interval being longer than the second time interval.

Abstract: A robust segmentation technique based on multi-layer classification technique to identify the lesion boundary is described. The inventors have discovered a technique based on training several classifiers such that to classify each pixel as lesion versus normal Each classifier is trained on a specific range of image resolutions. Then, for a new test image, the trained classifiers are applied on the image. Then by fusing the prediction results in pixel level a probability map is generated. In the next step, a thresholding method is applied to convert the probability map to a binary mask, which determines a mole border.

Abstract: A result format modifying method, system, and non-transitory computer readable medium, include an extracting circuit configured to extract a plurality of format types of a search result conducted by a user, a determining circuit configured to determine user activity based on user data, and a deciding circuit configured to decide a format of the plurality of format types to deliver to the user based on a time interval between a current time and a start time of the user's next activity as determined by the determining circuit.

Abstract: A method for computer-aided diagnosis of skin lesions includes obtaining a dermoscopic image, convolving the dermoscopic image in a plurality of convolutional layers, obtaining deconvolved outputs of at least two convolutional layers of the plurality of convolutional layers, obtaining side-output feature maps by applying loss functions to the deconvolved outputs of the at least two convolutional layers, obtaining a first concatenated feature map by concatenating the side-output feature maps with different first weights, obtaining a second concatenated feature map by concatenating the side-output feature maps with different second weights, and producing a final score map by convolving the first and second concatenated feature maps in a final convolutional layer followed by a loss layer. Also disclosed: a computer-readable medium embodying instructions for the method, and an apparatus configured to implement the method.

Abstract: A scan head for scanning skin includes a frame and a camera coupled to the frame. A controllable probe is coupled to the frame and is configured to change an orientation of hair on the skin to be examined and imaged with the camera.

Abstract: A computer-implemented screening method, system, and computer program product including detecting at least two disassembled components of an object spread across multiple sensor scan images of at least one container, storing a record of each disassembled component correlated with contextual information of each owner of each container corresponding to a sensor scan image, and flagging the owner of the container in the sensor scan image based on a joint assessment of the sensor scan image including a disassembled component that can be combined with another disassembled component in a different sensor scan image to assemble the object and the contextual information of each owner.

Abstract: A method for image analysis comprises receiving one or more images of a plurality of lesions captured from a body of a person, extracting one or more features of the plurality of lesions from the one or more images, analyzing the extracted one or more features, wherein the analyzing comprises determining a distance between at least two lesions with respect to the extracted one or more features, and determining whether any of the plurality of lesions is an outlier based on the analyzing.

Abstract: A method for risk assessment comprises receiving one or more images of a plurality of lesions captured from a body of a target person, generating one or more digital signatures based on the one or more images from the body of the target person, comparing the generated one or more digital signatures to digital signatures of respective reference persons, wherein the comparing comprises measuring similarities between the generated one or more digital signatures and the digital signatures of the respective reference persons, and determining a risk factor for the target person of developing a disease based on the measured similarities and predetermined risk factors of developing the disease for the reference persons.

Abstract: A method for image analysis comprises receiving one or more current images of a lesion from a body of a person, wherein the one or more current images are electronically captured by and transmitted from a capture device, and analyzing the one or more current images, wherein the analyzing comprises performing image processing to compare the one or more current images captured at a first time to one or more previous images of the lesion captured at a second time prior to the first time, and determining at least one difference between the one or more current images and the one or more previous images based on the comparing. The method further comprises determining a probability that the lesion will become diseased based on the analysis, and recommending a time for a future image capture of the lesion and/or a consultation with a practitioner based on the determined probability.

Abstract: A method for image analysis comprises receiving one or more images of a plurality of lesions captured from a body of a person, extracting one or more features of the plurality of lesions from the one or more images, analyzing the extracted one or more features, wherein the analyzing comprises determining a distance between at least two lesions with respect to the extracted one or more features, and determining whether any of the plurality of lesions is an outlier based on the analyzing.

Abstract: A structure-preserving composite model for skin lesion segmentation includes partitioning a dermoscopic image into superpixels at a first scale. Each superpixel is a vertex on a graph defined by color coordinates and spatial coordinates, and represents a number of pixels of the dermoscopic image according to the first scale. Further, constructing a plurality of k background templates by k-means clustering selected ones of the superpixels in space and color. Additionally, generating sparse representations of the plurality of superpixels based on the plurality of background templates. Also, calculating a reconstruction error for each superpixel by comparison of its sparse representation to its original color coordinates and spatial coordinates. Furthermore, outputting a confidence map that identifies each pixel of the dermoscopic image as belonging or not belonging to a skin lesion, based on the reconstruction errors of the representative superpixels.