Abstract: The present disclosure relates to a method and system for generating a road network. An embodiment of the present invention provides a method comprising: identifying a target area to be refined in a road network skeleton; and refining the target area using at least one trajectory associated with the target area to generate the road network. Another embodiment of the present invention provides a corresponding system.

Abstract: The present disclosure relates to the technical field of tea brewing devices, and more particularly, to a beverage brewing device. The beverage brewing device comprises a kettle body, a heating disc, and a tea-leaf basket. The heating disc and the tea-leaf basket are located in the kettle body and an air cylinder mechanism is fixed in the kettle body. A moving piston is arranged in an inner cavity of the air cylinder mechanism, and the piston is connected to the tea-leaf basket. The air cylinder mechanism is connected to an air pump, which is used for conveying a driving gas to the air cylinder mechanism. The piston is driven by the driving gas, thereby driving the tea-leaf basket to move in the kettle body. The air cylinder mechanism may automatically drive the tea-leaf basket to move up and down, achieving a simple structure and a low cost.

Abstract: Embodiments facilitating audio source identification are provided. A computer-implemented method comprises: receiving, by a device operatively coupled to one or more processors, an audio signal under inspection; generating, by the device, an image of time-frequency spectrum of low frequency component and high frequency component of the audio signal; and identifying, by the device, a source of the audio signal based on the generated image and one or more patterns of time-frequency spectrum, wherein each of the one or more patterns is corresponding to low frequency feature and high frequency feature of a specific audio source.

Abstract: Embodiments of the present invention facilitate product defect detection. A computer-implemented method comprises: receiving, by a device operatively coupled to one or more processors, a template image of a normal product; generating, by the device, one or more geometric training parameters for transforming the template image; and transforming, by the device, the template image using the one or more geometric training parameters to generate a transformed image for training a data model, wherein the trained data model being used for aligning the template image and an image under inspection of a product.

Abstract: Examples relate to identifying heartbeat messages. In one example, a computing device may: obtain a plurality of messages that includes incoming messages and outgoing messages, each incoming message being sent from a server device to a client device, and each outgoing message being sent from the client device to the server device; identify candidate message pairs, each candidate message pair including one incoming message and one outgoing message; and identify a heartbeat message pair from the candidate message pairs based on at least one of: plurality of timestamps that includes i) incoming message timestamps that each correspond to one of the incoming messages, and ii) outgoing message timestamps that each correspond to one of the outgoing messages; a number of occurrences of each candidate message pair included a message log; or characteristics of data included in the incoming message and outgoing message of each candidate message pair.

Abstract: A computer implemented method for surface defect inspection that includes recording an optical image of a surface including a defect; converting the optical image including the defect into a heat map; extracting a region of interest including the defect from the heat map; and comparing the region of interest including the defect from the heat map to a binary classification model using a sliding window based voting mechanism to determine if the defect is greater than or less than a threshold failure value.

Abstract: Scheduling automated visual inspection tasks includes capturing an image of a component to be inspected. A visual inspection model is formed with a model engine as a composite model of utility modules and functional modules to perform visual inspection of the image of the component. An abstract processing workflow of the visual inspection model is derived with a scheduler including dependencies between the utility modules and the functional modules. Performance of each of the functional modules is profiled with the scheduler by testing performance with available hardware resources to produce a performance profile. Parallel instances of each of the functional modules in a branch of the abstract processing workflow are scheduled with the scheduler according to the dependencies and the performance profiles. An indication of defects in the component is produced by processing the visual inspection model according to the scheduled functional modules.

Abstract: Methods and systems for classification of sequence data include warping training sequence data according to a warping pattern. A neural network is trained using the warped training sequence data. Input sequence data is warped according to the warping pattern. The warped input sequence data is classified using the trained neural network.

Abstract: Embodiments of the disclosure provide a fisheye lens. The fisheye lens can include a first lens group near an object side, a second lens group near an imaging plane, and an aperture diaphragm disposed between the first and second lens groups. The first lens group can include, disposed sequentially from the object side to the imaging plane, a negative meniscus spherical first lens, an aspherical second lens, and an aspherical third lens. The second lens group can include, disposed sequentially from the object side to the imaging plane, a positive meniscus spherical fourth lens, a fifth lens formed of a positive biconvex spherical lens and a negative biconcave spherical lens, and an aspherical sixth lens.

Abstract: A computer-implemented method is provided for image-based defect detection. The method includes performing, by a processor device, template matching and subtraction on a set of training images and at least one template image to obtain a set of difference images. The difference images have defects, if any, highlighted therein. The method further includes generating, by the hardware processor applying a binary classification model to each of the training images in the set, activation heatmaps. The method also includes identifying, by the hardware processor, rough defect areas of interest in the activation heatmaps. The method additionally includes super-imposing, by the hardware processor, the activation heatmaps onto the difference images to obtain a set of super-imposed images, and highlight, as true defect areas, any areas in the super-imposed images having the defects from the difference images that overlap with the rough defect areas of interest from the activation heatmaps.

Abstract: Methods and systems for detecting abnormal connectivity on a product are provided. The methods receive an inspection image of the product including a defect, match the inspection image with a template image of the product to locate a corresponding normal region in the template image and obtain a differential image between the inspection image and the normal region. The method further includes forming a regional mask image from component masks. Each of the component masks includes a binary image of the template image with only one kind of components of the product remaining. The regional mask image is a region in its corresponding component mask that corresponds to the normal region. The method further includes determining, based on a calculation using the differential image and the at least one regional mask image, at least one of: connectivity relationship, connectivity type and connectivity scale of abnormal connectivity on the product.

Abstract: A computer-implemented method is provided for image-based, self-guided object detection. The method includes receiving, by a processor device, a set of images. Each of the images has a respective grid thereon that is labeled regarding a respective object to be detected using grid level label data. The method further includes training, by the processor device, a grid-based object detector using the grid level label data. The method also includes determining, by the processor device, a respective bounding box for the respective object in each of the images, by applying local segmentation to each of the images. The method additionally includes training, by the processor device, a Region-based Convolutional Neural Network (RCNN) for joint object localization and object classification using the respective bounding box for the respective object in each of the images as an input to the RCNN.

Abstract: A method and an apparatus for generating a road network are disclosed. The method for generating a road network comprises: aggregating a plurality of grid cells partitioned in advance on a trajectory map based on trajectories in each grid cell of the plurality of grid cells to form level-1 regions; and generating a link of the road network by merging a level-1 region having two valid neighbors with its neighbor level-1 regions having two valid neighbors.

Abstract: Systems and methods for navigating in consideration of estimated air quality in an individual area of a geographic region includes receiving traffic data for the individual area and sensor data of environmental pollution sensors within the individual region.

Abstract: A mechanism is provided for controlling the internal air-quality of a vehicle. In-vehicle sensor data of a vehicle are acquired and the usage status of the vehicle is determined based on the acquired in-vehicle sensor data. Based on the acquired in-vehicle sensor data and the determined usage status, a changing trend of the in-vehicle air-quality is determined and responsive to the determined changing trend of the in-vehicle air-quality, a control system of the vehicle is signaled to control the usage status of the vehicle based on a control policy.

Abstract: A mechanism is provided for controlling the internal air-quality of a vehicle, including determining a changing trend of the in-vehicle air-quality based on acquired in-vehicle sensor data and usage status of the vehicle and responsive to the determined changing trend of the in-vehicle air-quality, signaling a control system of the vehicle to control the usage status of the vehicle based on a control policy.

Abstract: An apparatus or a method for detecting activity quantity of an object includes a sense unit, a count unit, a trigger unit, and a radio circuit. The sense unit senses movements of the object, and generates a sensing signal based on the sensed movements. The count unit receives the sensing signal from the sense unit, counts a number of the movements from the sensing signal, and generates a movement number signal including the number of the movements. The trigger unit generates a trigger signal based on whether one or more trigger conditions are satisfied. The radio circuit is triggered in response to the trigger signal, to generate an activity quantity signal based on the movement number signal and ID information corresponding to the object.

Abstract: A method and an apparatus for generating a road network are disclosed. The method for generating a road network comprises: aggregating a plurality of grid cells partitioned in advance on a trajectory map based on trajectories in each grid cell of the plurality of grid cells to form level-1 regions; and generating a link of the road network by merging a level-1 region having two valid neighbors with its neighbor level-1 regions having two valid neighbors.

Abstract: The present disclosure provides a method for characterizing ohmic contact electrode performance of a semiconductor device. The method comprises: preparing two sets of testing patterns on a semiconductor device; testing resistance values of the two sets of testing patterns respectively; calculating a sheet resistance of an ohmic contact area according to the obtained resistance values; and evaluating the ohmic contact electrode performance of the semiconductor device according to the sheet resistance of the ohmic contact electrode.

Abstract: Identifying transport-level encoded payloads includes identifying transport-level encoded payloads from a recorded script in a display, determining multiple decoding option for at least one of the transport-level encoded payloads where the multiple decoding options includes a recommended chain, and displaying multiple decoding options with at least one of the transport-level encoded payloads.