Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for off-policy evaluation of a control policy. One of the methods includes obtaining policy data specifying a control policy for controlling a source agent interacting with a source environment to perform a particular task; obtaining a validation data set generated from interactions of a target agent in a target environment; determining a performance estimate that represents an estimate of a performance of the control policy in controlling the target agent to perform the particular task in the target environment; and determining, based on the performance estimate, whether to deploy the control policy for controlling the target agent to perform the particular task in the target environment.

Abstract: Provided are a face feature point detection method, applied to an image processing device, where the image processing device stores a feature area detection model and a feature point detection model. The method includes: preprocessing a face image to be detected to obtain a preprocessed target face image; performing feature point extraction on the target face image according to the feature area detection model and the feature point detection model to obtain a target feature point coordinate located within a face feature area in the target face image; and performing coordinate transformation on the target feature point coordinate to obtain a face feature point coordinate corresponding to the face image to be detected. Further provided are a face feature point detection device, an equipment and a storage medium.

Abstract: This inventions provides an artificial intelligence (A.I.) identified measuring method for a semiconductor image, comprising the steps of: providing an original image of a semiconductor; identifying a type and/or a category of the original image by an artificial intelligence; introducing a predetermined dimension measuring mode corresponding to the identified type and/or the identified category to scan the original image to generate a measurement signal of the original image; and extracting a designated object from the original image to generate a specific physical parameter of the original image after operation based on a measurement signal of the designated object and the measurement signal of the original image.

Abstract: A method for image processing includes: receiving a third two-dimensional image and a depth image corresponding to the third two-dimensional image, wherein the third two-dimensional image and the depth image include a face; establishing a three-dimensional model of the face according to the depth image; rotating the three-dimensional model of the face by a first angle; projecting the three-dimensional model of the face rotated by the first angle to an image coordinate system of the third two-dimensional image; and building a three-dimensional model of a background region of the third two-dimensional image, processing a background region of an image projected to the image coordinate system of the third two-dimensional image to obtain a fourth image.

Abstract: An image generating apparatus includes: a display outputting an image; a memory storing one or more instructions; and a processor. The processor is configured to execute the one or more instructions to detect an object in an image including a plurality of frames, provide a plurality of candidate boundaries for masking the detected object, identify an optimal boundary by assessing the provided plurality of candidate boundaries, and generate a partial moving image with the object moving by using the optimal boundary.

Abstract: Methods and systems for recognition of repeating geometric units in a computer image are here disclosed. According to an aspect, a representation of a computer image is split into components and every component is analyzed to identify the role of this component on the computer image. Identified components could include but are not limited to: rooms, doors, furniture etc. In one embodiment components are identified based on the presence or absence of at least one other component. The presence of a door, in a non-limiting example, could be used to denote the presence of a room. In a further embodiment, the program may extract size and perimeter information necessary for estimating needed materials from a representation of a computer image.

Abstract: A location information reporting method includes: a first base station receives a first message from a core network device, where the first message includes first instruction information used to instruct to obtain location information of a terminal device, and the first base station and the core network device have a control plane connection established for the terminal device; and the first base station sends a second message to a second base station, where the second message includes second instruction information, the second instruction information is used to instruct to obtain the location information of the terminal device, and the second base station is configured to provide a service for the terminal device at a current moment.

Abstract: According to one embodiment, a reading system includes an extractor, a determiner, and a reader. The extractor extracts a candidate image from an input image. The candidate image is a candidate of a portion of the input image in which a segment display is imaged. The determiner uses the candidate image and a mask to calculate a match ratio indicating a certainty of a segment display being included in the candidate image, and determines that the candidate image is an image of a segment display when the match ratio is not less than a threshold. The mask and the threshold are preset. The reader reads a numerical value displayed in a segment display from the candidate image determined to be an image of a segment display.

Abstract: An image processing apparatus includes a measurement area setting unit that sets a measurement area in an input image, a small image setting unit that sets a small image in the input image based on the measurement area, a first estimation unit that estimates a flow distribution of a target in the small image, and a second estimation unit that estimates the number of targets to pass through the measurement area based on the flow distribution in the small image.

Abstract: A computing system is disclosed including a convolutional neural configured to receive an input that describes a facial image and generate a facial object recognition output that describes one or more facial feature locations with respect to the facial image. The convolutional neural network can include a plurality of convolutional blocks. At least one of the convolutional blocks can include one or more separable convolutional layers configured to apply a depthwise convolution and a pointwise convolution during processing of an input to generate an output. The depthwise convolution can be applied with a kernel size that is greater than 3×3. At least one of the convolutional blocks can include a residual shortcut connection from its input to its output.

Abstract: In a communications method of a wearable device, if a second BLUETOOTH connection between user equipment and the wearable device is disconnected, a first BLUETOOTH connection between a network connection device and the wearable device is established, so that the network connection device may send, to the wearable device through the first BLUETOOTH connection, first information sent by the user equipment through a third communication connection to the network connection device. In this way, indirect communication between the user equipment and the wearable device is implemented by using the network connection device, so that the user equipment and the wearable device are not limited by a communication range.

Abstract: A method and system generate an ensemble image representation for cross-domain retrieval of a fashion item image from a database by using a three-stream Siamese triplet loss trained convolutional neural network to generate a first retrieval descriptor corresponding to an inputted query image; using an average precision loss trained convolutional neural network to generate a second retrieval descriptor corresponding to the inputted query image; concatenating both the first retrieval descriptor and the second retrieval descriptor; and I2-normalizing the concatenated result to generate the ensemble image representation. During a first stage of the method and system, database items are cropped using a trained fine-grained fashion item detector.

Abstract: A method and an apparatus for outputting data are provided. The method includes: obtaining a set of human-face key point data, where the human-face key point data characterizes a position of a key point of a human face in a target human-face image; determining human-eye feature data for characterizing a shape feature of a human eye, based on the set of the human-face key point data; and inputting the human-eye feature data into a human-eye size recognition model obtained by pre-training to obtain a degree value for characterizing a size of the human eye, and outputting the degree value. The human-eye size recognition model characterizes a correspondence between human-eye feature data and a degree value. With the above method, the human-face key point data is effectively utilized to determine the size of the human eye, improving the accuracy of recognizing the size of the human eye.

Abstract: Disclosed are systems and methods for detecting a printer jam. The systems and methods can include receiving a reference image of a printer opening and a second image of the printer opening. A lack of a receipt between the second image compared to the reference image can be detected. The lack of the receipt can indicate the printer jam. After detecting the printer jam, operation of the self-service terminal can be terminated.

Abstract: A method includes training, using at least one processor, a specialized teacher model to perform visual object instance segmentation in order to segment and classify objects in first training images. The first training images contain foreground objects without backgrounds. The method also includes training, using the at least one processor, a student model to perform visual object instance segmentation in order to segment and classify objects in second training images. The second training images contain the foreground objects and the backgrounds. Training the student model includes using selected outputs of the specialized teacher model. The method further includes deploying the trained student model to perform visual object instance segmentation in an external device.

Abstract: A method and an electronic device employing an uninterrupted media play and call management system (UMPCMS) are provided for managing an incoming call without interrupting playing of media on the electronic device. The UMPCMS receives an indication of the incoming call, generates a notification object with one or more call management options for the incoming call in a configurable format based on preconfigured criteria, and overlays the generated notification object with the call management options on a graphical user interface (GUI) provided by the UMPCMS, while supporting continued playing of the media on the electronic device via the GUI without interruption by the incoming call. The UMPCMS receives a selection of a call management option from the electronic device and performs one or more executable actions on the incoming call and/or the playing of the media on the electronic device based on the received selection of the call management option.

Abstract: In embodiments, obtaining a plurality of image sets associated with a geographical region and a time period, wherein each image set of the plurality of image sets comprises multi-spectral and time series images that depict a respective particular portion of the geographical region during the time period, and predicting presence of a crop at particular locations within the particular portion of the geographical region associated with an image set of the plurality of image sets. Determining crop boundary locations within the particular portion of the geographical region based on the predicted presence of the crop at the particular locations, and generating a crop indicative image comprising at least one image of the multi-spectral and time series images of the image set overlaid with indication of crop areas, wherein the crop areas are defined by the determined crop boundary locations.

Abstract: A system and method for providing unsupervised domain adaption for spatio-temporal action localization that includes receiving video data associated with a surrounding environment of a vehicle. The system and method also include completing an action localization model to model a temporal context of actions occurring within the surrounding environment of the vehicle based on the video data and completing an action adaption model to localize individuals and their actions and to classify the actions based on the video data. The system and method further include combining losses from the action localization model and the action adaption model to complete spatio-temporal action localization of individuals and actions that occur within the surrounding environment of the vehicle.

Abstract: A method for inspecting a pillar-shaped honeycomb formed body before firing includes a step a1 of capturing at least one of a first end surface and a second end surface of a pillar-shaped honeycomb formed body before firing with a camera to generate an image of the at least one of the first end surface and the second end surface; a step b1 of measuring a size of an opening of a plurality of cells in the image generated by step a1; and a step c1 of identifying abnormal cells with the opening having a size deviating from a predetermined allowable range from the cells based on a measurement result of step b1, and measuring a number of the abnormal cells.

Abstract: Systems and methods provide editing operations in a smart editing system that may generate a focal point within a mask of an object for each frame of a video segment and perform editing effects on the frames of the video segment to quickly provide users with natural video editing effects. An eye-gaze network may produce a hotspot map of predicted focal points in a video frame. These predicted focal points may then be used by a gaze-to-mask network to determine objects in the image and generate an object mask for each of the detected objects. This process may then be repeated to effectively track the trajectory of objects and object focal points in videos. Based on the determined trajectory of an object in a video clip and editing parameters, the editing engine may produce editing effects relative to an object for the video clip.