Abstract: A mobile device can generate real-time complex visual image effects using asynchronous processing pipeline. A first pipeline applies a complex image process, such as a neural network, to keyframes of a live image sequence. A second pipeline generates flow maps that describe feature transformations in the image sequence. The flow maps can be used to process non-keyframes on the fly. The processed keyframes and non-keyframes can be used to display a complex visual effect on the mobile device in real-time or near real-time.

Abstract: A machine learning system can generate an image mask (e.g., a pixel mask) comprising pixel assignments for pixels. The pixels can he assigned to classes, including, for example, face, clothes, body skin, or hair. The machine learning system can be implemented. using a convolutional neural network that is configured to execute efficiently on computing devices having limited resources, such as mobile phones. The pixel mask can be used to more accurately display video effects interacting with a user or subject depicted in the image.

Abstract: Among other things, embodiments of the present disclosure improve the functionality of computer software and systems by facilitating the automatic performance optimization of a software application based on the particular platform upon which the application runs. In some embodiments, the system can automatically choose a set of parameters or methods at run-time from a design space with pre-selected optimization methods and parameters (e.g., algorithms, software libraries, and/or hardware accelerators) for a specific task.

Abstract: An absorbable endoluminal stent and method for preparing the same are provided in the present invention. The absorbable endoluminal stent comprises a stent body, a plurality of through holes formed in the stent body, and bioabsorbable polymeric materials filled in the through holes. When the stent is implanted into the blood vessels, damages on stent caused during crimping and expansion processes are reduced. Radical supporting force duration of stent is improved and mechanical properties of stent after implantation are guaranteed by compositing the materials in the through holes and materials of the stent body.

Abstract: Remote distribution of multiple neural network models to various client devices over a network can be implemented by identifying a native neural network and remotely converting the native neural network to a target neural network based on a given client device operating environment. The native neural network can be configured for execution using efficient parameters, and the target neural network can use less efficient but more precise parameters.

Abstract: A machine learning system can generate an image mask (e.g., a pixel mask) comprising pixel assignments for pixels. The pixels can be assigned to classes, including, for example, face, clothes, body skin, or hair. The machine learning system can be implemented using a convolutional neural network that is configured to execute efficiently on computing devices having limited resources, such as mobile phones. The pixel mask can be used to more accurately display video effects interacting with a user or subject depicted in the image.

Abstract: Remote distribution of multiple neural network models to various client devices over a network can be implemented by identifying a native neural network and remotely converting the native neural network to a target neural network based on a given client device operating environment. The native neural network can be configured for execution using efficient parameters, and the target neural network can use less efficient but more precise parameters.

Abstract: A mobile device can generate real-time complex visual image effects using asynchronous processing pipeline. A first pipeline applies a complex image process, such as a neural network, to keyframes of a live image sequence. A second pipeline generates flow maps that describe feature transformations in the image sequence. The flow maps can be used to process non-keyframes on the fly. The processed keyframes and non-keyframes can be used to display a complex visual effect on the mobile device in real-time or near real-time.

Abstract: A mobile device can generate real-time complex visual image effects using asynchronous processing pipeline. A first pipeline applies a complex image process, such as a neural network, to keyframes of a live image sequence. A second pipeline generates flow maps that describe feature transformations in the image sequence. The flow maps can be used to process non-keyframes on the fly. The processed keyframes and non-keyframes can be used to display a complex visual effect on the mobile device in real-time or near real-time.

Abstract: Systems and methods are provided for initiating transfer of image data corresponding to at least one predetermined level of an image pyramid comprising higher resolution to a graphic processing unit (GPU) of the computing device, calculating, by the central processing unit (CPU) of the computing device, optical flow of at least one predetermined coarse level of the image pyramid, transferring, by the CPU of the computing device, the calculated optical flow of the at least one predetermined coarse level of the image pyramid to the GPU, calculating, by the GPU of the computing device, the optical flow of the at least one predetermined level of the image pyramid comprising higher resolution, and outputting, by the GPU of the computing device, the optical flow of the image data.

Abstract: Among other things, embodiments of the present disclosure improve the functionality of computer software and systems by facilitating the automatic performance optimization of a software application based on the particular platform upon which the application runs. In some embodiments, the system can automatically choose a set of parameters or methods at run-time from a design space with pre-selected optimization methods and parameters (e.g., algorithms, software libraries, and/or hardware accelerators) for a specific task.

Abstract: A machine learning system can generate an image mask (e.g., a pixel mask) comprising pixel assignments for pixels. The pixels can be assigned to classes, including, for example, face, clothes, body skin, or hair. The machine learning system can be implemented using a convolutional neural network that is configured to execute efficiently on computing devices having limited resources, such as mobile phones. The pixel mask can be used to more accurately display video effects interacting with a user or subject depicted in the image.

Abstract: A mobile device can generate real-time complex visual image effects using asynchronous processing pipeline. A first pipeline applies a complex image process, such as a neural network, to keyframes of a live image sequence. A second pipeline generates flow maps that describe feature transformations in the image sequence. The flow maps can be used to process non-keyframes on the fly. The processed keyframes and non-keyframes can be used to display a complex visual effect on the mobile device in real-time or near real-time.

Abstract: A computer program product for provisioning resources in a balanced data transfer pipeline may associate a first requested task with a first category, allocate a first resource of a data path to the first requested task based on the first resource corresponding to the first category; and allocate a second resource as part of the data path to the first requested task based on the second resource corresponding to the first category, wherein the first resource corresponds to a first segment of the data path and the second resource corresponds to a second segment of the data path.

Abstract: A computer program product for provisioning resources in a balanced data transfer pipeline may associate a first requested task with a first category, allocate a first resource of a data path to the first requested task based on the first resource corresponding to the first category; and allocate a second resource as part of the data path to the first requested task based on the second resource corresponding to the first category, wherein the first resource corresponds to a first segment of the data path and the second resource corresponds to a second segment of the data path.

Abstract: An absorbable endoluminal stent and method for preparing the same are provided in the present invention. The absorbable endoluminal stent comprises a stent body, a plurality of through holes formed in the stent body, and bioabsorbable polymeric materials filled in the through holes. When the stent is implanted into the blood vessels, damages on stent caused during crimping and expansion processes are reduced. Radical supporting force duration of stent is improved and mechanical properties of stent after implantation are guaranteed by compositing the materials in the through holes and materials of the stent body.

Abstract: Methods, systems and computer program products for data fetching in a networked computing environment. In one embodiment, the method comprises receiving a request from an analytical node for a set of data for a defined job, and identifying in networked storage a subset of the data for the job. The subset of data is loaded to the analytical node based on the sequence in which the data are projected to be accessed in the job. In an embodiment, the request includes a specification for the job, and the specification is analyzed to identify the subset of data. In one embodiment, the subset of data is identified by identifying another job having a relationship to the defined job, and identifying the data used for that other job. In an embodiment, the networked computing environment is a cloud computing environment, and the defined job is an analytics job.

Abstract: A computer program product for provisioning resources in a balanced data transfer pipeline may associate a first requested task with a first category, allocate a first resource of a data path to the first requested task based on the first resource corresponding to the first category; and allocate a second resource as part of the data path to the first requested task based on the second resource corresponding to the first category, wherein the first resource corresponds to a first segment of the data path and the second resource corresponds to a second segment of the data path.

Abstract: A computer program product for provisioning resources in a balanced data transfer pipeline may associate a first requested task with a first category, allocate a first resource of a data path to the first requested task based on the first resource corresponding to the first category; and allocate a second resource as part of the data path to the first requested task based on the second resource corresponding to the first category, wherein the first resource corresponds to a first segment of the data path and the second resource corresponds to a second segment of the data path.

Abstract: A memory control unit of a turbo code decoder includes a buffer having a plurality of storage slots, a buffer control operatively coupled to the buffer, a router operatively coupled to the buffer control and to a plurality of data sources, and a conflict detection unit operatively coupled to the router, to the buffer control, and to the plurality of data sources. The buffer temporarily stores information intended for storage in a memory bank. The buffer control determines a number of available storage slots in the buffer. The router routes data from the data sources to the buffer control. The conflict detection unit initiates a temporary halt of some of the data sources when the number of available storage slots is insufficient to store all of the data from data sources attempting to access the memory bank.