Abstract: A device and method of operating the device for automatically creating photos or videos of a certain moment are provided. The method includes obtaining a plurality of image frames sequentially captured through a camera for a preset time interval; detecting at least one image frame among the plurality of image frames in which a main object corresponding to a preset main object or an action of the main object corresponding to a preset action is recognized; determining a type of composition of the at least one image frame; cropping a region including the main object from the at least one image frame based on placement of objects in the at least one image frame and the determined type of composition; and creating the photo using the cropped region.

Abstract: Jigs for guiding femur and tibia resectioning in knee surgery contain bone-jig contact surfaces and a cutting guide as a single unitary piece. Contact surfaces are curvilinear surfaces formed into ends of projections from a jig base. Each jig has three pairs of contact surfaces selected to abut low-wear, lateral and medial, articular surface features, such that only one self-locking position against the bone (or cartilage) is possible and the integral cutting guide will define only one cut plane for the resectioning. An improved rotational transformation that converts scan views into desired proper axes is based on projections of rotated coordinates onto the plane of rotation to produce parameters that closely correspond to the joint surfaces in the desired jig coordinates.

Abstract: Embodiments of the present disclosure relate to a texture unit circuit in a neural processor circuit. The neural processor circuit includes a tensor access operation circuit with the texture unit circuit, a data processor circuit, and at least one neural engine circuit. The texture unit circuit fetches a source tensor from a system memory by referencing an index tensor in the system memory representing indexing information into the source tensor. The data processor circuit stores an output version of the source tensor obtained from the tensor access operation circuit and sends the output version of the source tensor as multiple of units of input data to the at least one neural engine circuit. The at least one neural engine circuit performs at least convolution operations on the units of input data and at least one kernel to generate output data.

Abstract: A robot configured to perceive a model of an environment, including: a chassis; a set of wheels; a plurality of sensors; a processor; and memory storing instructions that when executed by the processor effectuates operations including: capturing a plurality of data while the robot moves within the environment; perceiving the model of the environment based on at least a portion of the plurality of data, the model being a top view of the environment; storing the model of the environment in a memory accessible to the processor; and transmitting the model of the environment and a status of the robot to an application of a smartphone previously paired with the robot.

Abstract: The technology disclosed relates to artificial intelligence-based determination of analyte data for base calling. In particular, the technology disclosed uses input image data that is derived from a sequence of images. Each image in the sequence of images represents an imaged region and depicts intensity emissions indicative of one or more analytes and a surrounding background of the intensity emissions at a respective one of a plurality of sequencing cycles of a sequencing run. The input image data comprises image patches extracted from each image in the sequence of images. The input image data is processed through a neural network to generate an alternative representation of the input image data. The alternative representation is processed through an output layer to generate an output indicating properties of respective portions of the imaged region.

Abstract: Embodiments are directed to managing machine learning models. Domain items may be determined based on domain data and schema information. Labels that correspond to a predicted outcome may be generated based on the domain data. A model may be trained based on a portion of a plurality of feature records and the labels such that each feature record may be associated with an observance of a domain item. The trained model may be disqualified based on evaluation metrics that may be below a threshold value causing further actions, including: submitting other portions of the feature records to the disqualified model; determining erroneous feature fields in the feature records based on metrics associated with the submission of the other portions of feature records; updating the feature records to exclude the erroneous feature fields; retraining the disqualified model based on the updated feature records.

Abstract: An image processing device including a storage unit configured to store an object detection neural network trained using a first K-channel image generated from a first M-channel image and a first N-channel image generated from the first M-channel image, a reception unit configured to receive, from a sensor, a second M-channel image and a second N-channel image that include an identical subject, and an image analysis unit configured to generate, using the object detection neural network trained using the first K-channel image, object detection result information with respect to a second K-channel image generated from the second M-channel image and the second N-channel image, and output the object detection result information.

Abstract: A computerized system and method of modeling myocardial tissue perfusion can include acquiring a plurality of original frames of magnetic resonance imaging (MRI) data representing images of a heart of a subject and developing a manually segmented set of ground truth frames from the original frames. Applying training augmentation techniques to a training set of the originals frame of MRI data can prepare the data for training at least one convolutional neural network (CNN). The CNN can segment the training set of frames according to the ground truth frames. Applying the respective input test frames to a trained CNN can allow for segmenting an endocardium layer and an epicardium layer within the respective images of the input test frames. The segmented images can be used in calculating myocardial blood flow into the myocardium from segmented images of the input test frames.

Abstract: Automatic substance preparation and evaluation systems and methods are provided for preparing and evaluating a fluidic substance, such as e.g. a sample with bodily fluid, in a container and/or in a dispense tip. The systems and methods can detect volumes, evaluate integrities, and check particle concentrations in the container and/or the dispense tip.

Abstract: Systems and methods for video processing are described. Embodiments of the present disclosure generate a plurality of image feature vectors corresponding to a plurality of frames of a video; generate a plurality of low-level event representation vectors based on the plurality of image feature vectors, wherein a number of the low-level event representation vectors is less than a number of the image feature vectors; generate a plurality of high-level event representation vectors based on the plurality of low-level event representation vectors, wherein a number of the high-level event representation vectors is less than the number of the low-level event representation vectors; and identify a plurality of high-level events occurring in the video based on the plurality of high-level event representation vectors.

Abstract: Methods, systems, and apparatus, including computer-readable media, are described for performing neural network computations using a system configured to implement a neural network on a hardware circuit. The system includes a host that receives a batch of inputs to a neural network layer. Each of the inputs is stored in a memory location identified by an address. The system identifies one or more duplicate addresses in a listing of addresses for one or more inputs. For each duplicate address: the system generates a unique identifier that identifies the duplicate address in the listing of addresses. The system (i) obtains first inputs from memory locations identified by addresses corresponding to the unique identifiers and (ii) generates an output of the layer from the obtained first inputs.

Abstract: Provided is a method of identifying a hand of a genuine user wearing a wearable device. According to an embodiment, the method includes using a sensor included in the wearable device to recognize a hand located in a detection area of the sensor; estimating a position of a shoulder connected to the recognized hand based on a positional relation between the orientation of the recognized hand and at least one body part connected to the recognized hand; and using information about a probability of a shoulder of the genuine user being present in the estimated position to determine whether the recognized hand is a hand of the genuine user.

Abstract: There is described a computer-implemented method and system for classifying images, the computer-implemented method comprising: receiving an image to be classified, generating a vector representation of the image to be classified using an image embedding method, comparing the vector representation of the image to predefined vector representations of the predefined image categories, and identifying a relevant category amongst the predefined image categories based on the comparison, the relevant category being associated with the image to be classified and outputting the relevant category.

Abstract: Methods, systems, and computer programs are presented for adding new features to a network service. A method includes receiving an image depicting an object of interest. A category set is determined for the object of interest and an image signature is generated for the image. Using the category set and the image signature, the method identifies a set of publications within a publication database and assigns a rank to each publication. The method causes presentation of the ranked list of publications at a computing device from which the image was received.

Abstract: Disclosed are a fill light device, a method for controlling a fill light device, and a computer readable storage medium. The fill light device includes a flash light; and a light guide, the light guide being located on a light-exiting side of the flash light and being configured to be controlled to change a shape and/or a light-transmitting area to change a light-exiting area and/or a light-emitting angle of the fill light device. The method includes obtaining a control parameter of the light guide; and changing a shape and/or a light-transmitting area of the light guide according to the control parameter to change a light-exiting area and/or a light-emitting angle of the fill light device.

Abstract: An image processing method, device, storage medium and camera are provided. The method, applied to the camera, comprises: capturing a target image; acquiring a target feature map of the target image through a preset target convolution layer, wherein the target convolution layer includes at least one of a plurality of convolution layers of a convolutional neural network (CNN); and outputting the target feature map. That is to say, after the target image is captured by the camera, the target feature map may be acquired by processing the target image through the target convolution layer pre-integrated in the camera. In this way, the camera transmits the target feature map only to reduce the transmitted data volume, thereby being capable of shortening transmission delay and saving bandwidth required by image transmission.

Abstract: Disclosed herein is a system and method for augmenting data by generating a plurality of pose-altered images of an item from one or more 2D images of the item and using the augmented data to train a train a feature extractor. In other aspects of the invention, the trained feature extractor is used to enroll features extracted from images of new products in a library database of known products or to identify images of unknown products by matching features of an image of the unknown product with features stored in the library database.

Abstract: An information processing device is configured to output work information related to work performed by a serving person, the information processing device including an image acquisition unit configured to acquire an original image including a served person and a plurality of served objects that the serving person serves, an image division unit configured to divide the original image into a served-person image, in which the served person is captured, and a plurality of served-object images, in which each served object is captured, a scene estimation unit configured to estimate a scene, which is the situation the serving person is in, by using a first trained model, a chunk estimation unit configured to estimate a chunk, which is information dividing or suggesting the work information, by using one of a plurality of second trained models, and an output unit configured to output the chunk.

Abstract: In a case where the operation program is started, a CPU of the mini-batch learning apparatus functions as a calculation unit, a specifying unit, and an update unit. The calculation unit calculates an area ratio of each of a plurality of classes in mini-batch data. The specifying unit specifies a rare class of which the area ratio is lower than a setting value. The update unit sets an update level of the machine learning model in a case where the rare class is specified by the specifying unit to be lower than an update level of the machine learning model in a case where the rare class is not specified by the specifying unit.

Abstract: Techniques are disclosed for identifying and presenting video content that demonstrates features of a target product. The video content can be accessed, for example, from a media database of user-generated videos that demonstrate one or more features of the target product so that a user can see and hear the product in operation via a product webpage before making a purchasing decision. The product functioning videos supplement any static images of the target product and the textual product description to provide the user with additional context for each of the product's features, depending on the textual product description. The user can quickly and easily interact with the product webpage to access and playback the product functioning video to see and/or hear the product in operation.