Abstract: A computer vision processor of a camera extracts attributes of persons or vehicles from hyperzooms generated from image frames. The hyperzooms represent traffic patterns. The extracting is performed using a feature extractor of an on-camera convolutional neural network (CNN) including an inverted residual structure. The attributes include at least colors of clothing of the persons or colors of the vehicles. Mobile semantic segmentation models of the CNN are generated using the hyperzooms and the attributes. Attribute analytics are generated by executing the mobile semantic segmentation models while obviating network usage by the camera. The attribute analytics are stored in a key-value database located on a memory card of the camera. A query is received from the server instance specifying one or more of the attributes. The attribute analytics are filtered using the one or more of the attributes to obtain a portion of the traffic patterns.

Abstract: A computer vision processor of a camera generates hyperzooms for persons or vehicles from image frames captured by the camera. The hyperzooms include a first hyperzoom associated with the persons or vehicles. The computer vision processor tracks traffic patterns of the persons or vehicles while obviating network usage by the camera by predicting positions of the persons or vehicles using a Kalman Filter from the first hyperzoom. The persons or vehicles are detected in the second hyperzoom. The positions of the persons or vehicles are updated based on detecting the persons or vehicles in the second hyperzoom. The first hyperzoom is removed from the camera. Tracks of the persons or vehicles are generated based on the updated positions. The second hyperzoom is removed from the camera. Track metadata is generated from the tracks for storing in a key-value database located on a non-transitory computer-readable storage medium of the camera.

Abstract: A computer vision processor of a camera extracts attributes of persons or vehicles from hyperzooms generated from image frames. The hyperzooms represent traffic patterns. The extracting is performed using a feature extractor of an on-camera convolutional neural network (CNN) including an inverted residual structure. The attributes include at least colors of clothing of the persons or colors of the vehicles. Mobile semantic segmentation models of the CNN are generated using the hyperzooms and the attributes. Attribute analytics are generated by executing the mobile semantic segmentation models while obviating network usage by the camera. The attribute analytics are stored in a key-value database located on a memory card of the camera. A query is received from the server instance specifying one or more of the attributes. The attribute analytics are filtered using the one or more of the attributes to obtain a portion of the traffic patterns.

Abstract: A script-to-movie generation method for a computing device includes obtaining a movie script, generating a video according to the movie script, optimizing the generated video until a pass condition is satisfied, and outputting the optimized video.

Abstract: A computer vision processor of a camera extracts attributes of persons or vehicles from hyperzooms generated from image frames. The hyperzooms represent traffic patterns. The extracting is performed using a feature extractor of an on-camera convolutional neural network (CNN) including an inverted residual structure. The attributes include at least colors of clothing of the persons or colors of the vehicles. Mobile semantic segmentation models of the CNN are generated using the hyperzooms and the attributes. Attribute analytics are generated by executing the mobile semantic segmentation models while obviating network usage by the camera. The attribute analytics are stored in a key-value database located on a memory card of the camera. A query is received from the server instance specifying one or more of the attributes. The attribute analytics are filtered using the one or more of the attributes to obtain a portion of the traffic patterns.

Abstract: A script-to-movie generation method for a computing device includes obtaining a movie script, generating a video according to the movie script, optimizing the generated video until a pass condition is satisfied, and outputting the optimized video.

Abstract: A method for generating speech animation from an audio signal includes: receiving the audio signal; transforming the received audio signal into frequency-domain audio features; performing neural-network processing on the frequency-domain audio features to recognize phonemes, wherein the neural-network processing is performed using a neural network trained with a phoneme dataset comprising of audio signals with corresponding ground-truth phoneme labels; and generating the speech animation from the recognized phonemes.

Abstract: A method for generating speech animation from an audio signal includes: receiving the audio signal; transforming the received audio signal into frequency-domain audio features; performing neural-network processing on the frequency-domain audio features to recognize phonemes, wherein the neural-network processing is performed using a neural network trained with a phoneme dataset comprising of audio signals with corresponding ground-truth phoneme labels; and generating the speech animation from the recognized phonemes.

Abstract: The disclosure relates to a BCMA-targeting chimeric antigen receptor and uses thereof. Specifically, the disclosure provides a polynucleotide sequence selected from the group consisting of: (1) a polynucleotide sequence comprising, linked in sequence, a sequence encoding an anti-BCMA single chain antibody, a sequence encoding the hinge region of human CD8?, a sequence encoding the transmembrane region of human CD8, a sequence encoding the intracellular domain of human 41BB, a sequence encoding the intracellular domain of human CD3? and optionally a sequence encoding a fragment of EGFR comprising the extracellular domain III and the extracellular domain IV; and (2) a complementary sequence of the polynucleotide sequence of (1). The disclosure further provides corresponding fusion proteins and vectors comprising the coding sequence, as well as uses of the fusion proteins, coding sequences and vectors.

Abstract: Embodiments of this specification disclose systems and methods for automotive part recognition based on a vehicle damage assessment image. A method includes: obtaining a damage assessment image of a target vehicle; obtaining an automotive part list of the target vehicle based on a vehicle identification code of the target vehicle, wherein the automotive part list comprises customized configuration information of automotive parts of the target vehicle; and determining a damaged automotive part of the target vehicle from the damage assessment image based on the customized configuration information of the automotive parts of the target vehicle and an image recognition algorithm, to obtain an automotive part identification serial number of the determined damaged automotive part.

Abstract: Embodiments of this specification disclose a method and an apparatus for automotive part recognition based on a vehicle damage assessment image. The method includes: determining a damaged automotive part of a vehicle by recognizing a damage assessment image of the vehicle based on an image recognition algorithm; obtaining an automotive part list of the vehicle, wherein the automotive part list comprises a plurality of automotive parts corresponding to a plurality of automotive part identification serial numbers; matching the damaged automotive part with the plurality of automotive parts in the automotive part list to determine an automotive part corresponding to the damaged automotive part; and outputting an automotive part identification serial number of the determined automotive part.

Abstract: Embodiments of this specification disclose a method and an apparatus for automotive part recognition based on a vehicle damage assessment image. The method includes: determining a damaged automotive part of a vehicle by recognizing a damage assessment image of the vehicle based on an image recognition algorithm; obtaining an automotive part list of the vehicle, wherein the automotive part list comprises a plurality of automotive parts corresponding to a plurality of automotive part identification serial numbers; matching the damaged automotive part with the plurality of automotive parts in the automotive part list to determine an automotive part corresponding to the damaged automotive part; and outputting an automotive part identification serial number of the determined automotive part.

Abstract: Embodiments of this specification disclose systems and methods for automotive part recognition based on a vehicle damage assessment image. A method includes: obtaining a damage assessment image of a target vehicle; obtaining an automotive part list of the target vehicle based on a vehicle identification code of the target vehicle, wherein the automotive part list comprises customized configuration information of automotive parts of the target vehicle; and determining a damaged automotive part of the target vehicle from the damage assessment image based on the customized configuration information of the automotive parts of the target vehicle and an image recognition algorithm, to obtain an automotive part identification serial number of the determined damaged automotive part.

Abstract: A mobile device generates a first representation, based on a model, of a first content received by the mobile device from a website. An online system receives the representation of the content from the mobile device. The online system receives a second content from the website and generates a representation of the second content using the model. The online system compares the representation of the first content with the representation of the second content to determine a distance between the two representations. The distance indicates a level of similarity between the first content and the second content. The online system compares the distance between the representation of the first content and representation of the second content to determine if the distance exceeds a threshold distance. If the distance exceeds the threshold distance, the online system prevents other mobile devices from accessing the website.

Abstract: An online system transmits to a mobile device a feed story that includes a uniform resource locator (URL) of a feed story website. The online system receives from the mobile device a URL log that includes URLs that the mobile device accessed in response to requesting content from the feed story website. The online system extracts a feature of at least one URL in the log, and inputs the extracted feature into a model that was trained, using machine learning, to identify websites that perform cloaking. The model generates a score indicating a likelihood that the feed story website performs cloaking based the extracted feature. The online system compares the score to a threshold to determine whether the feed story website performs cloaking. If the online system determines that the feed story website performs cloaking, the online system limits delivery of content including the URL of the feed story website.

Abstract: In one embodiment, the wireless charger can be light-weight, thin, and can be hidden and/or integrated inside of handbags, backpacks, jackets, and other accessories. The wireless charger can also be used as a standalone product. The wireless charger charges phones using wireless power transmission and incorporates a battery which can be recharged through a power adapter. When properly integrated, the wireless charger according to embodiments described herein can be integrated into such apparel, accessories, or other products without altering or affecting the appearance of the product. For example, the wireless charger may be seamlessly incorporated into most any apparel and accessories from purses to apparel to jackets if the product has a pocket. Because various aspects of the wireless charger are adaptable, it can be easily customized to meet customer needs.

Abstract: Disclosed is a method for monitoring security of a terminal system, including the following steps: monitoring a current running program in real time, and determining whether there is a security risk in the current running program; acquiring a corresponding preset risk score according to a type of the security risk, and adding the corresponding preset risk score to an accumulative risk score when there is the security risk in the current running program; and performing a risk prompt and a static scanning prompt when the accumulative risk score is greater than or equal to a risk threshold.

Abstract: Aspects of present disclosure relates to a binocular pedestrian detection system (BPDS). BPDS includes: a binocular camera to capture certain binocular images of pedestrians passing through a predetermined area, an image/video processing ASIC to process binocular images captured, and a binocular pedestrian detection system controller having a processor, a network interface, and a memory storing computer executable instructions. When executed by processor, computer executable instructions cause processor to perform: capturing, by binocular camera, binocular images of pedestrians, binocularly rectifying binocular images, calculating disparity maps of binocular images rectified, training a dual-stream deep learning neural network, and detecting pedestrians passing through predetermined area using dual-stream deep learning neural network trained.

Abstract: In one embodiment, a method includes receiving a request for a web page; sending a first response portion for generating the requested web page to a client computing device that includes a structured document place-holder code segments and executable code for implementing a page-assembling process; generating second response portions each for generating a corresponding portion of the requested web page that each include a call to a function of the page-assembling process; determining relative priorities of the second response portions; sending the second response portions to the client computing device in an order based on the determined relative priorities; and wherein the page-assembling process is configured to insert, or cause to be inserted, at a location determined by a corresponding one of the place-holder code segments, the second portions of content into a model representation of the structured document generated by a client rendering application.

Abstract: Embodiments herein relate to methods for sludge reduction for pretreatment of nitrotoluene wastewater using electro-catalytic redox. The embodiments may include (a) adjusting a pH of the nitrotoluene wastewater to 1.5 to 2.0, standing for precipitation, draining sludge of the nitrotoluene wastewater at the bottom, obtaining supernatant of nitrotoluene wastewater, placing the supernatant through a cathode inlet into a cathode chamber of an electrochemical reactor; (b) performing electrochemical treatment, wherein reduction reaction of the supernatant of the nitrotoluene wastewater takes place at the cathode chamber, the nitrotoluene wastewater is placed into the anode chamber for oxidation reaction through the cathode outlet, the catholyte tank, and the anode inlet in sequence; (c) adjusting the nitrotoluene wastewater treated in step (b) via the anolyte tank, and then discharging the nitrotoluene wastewater into a biochemical system.