Abstract: Computer vision systems and methods for text classification are provided. The system detects a plurality of text regions in an image and generates a bounding box for each detected text region. The system utilizes a neural network to recognize text present within each bounding box and classifies the recognized text, based on at least one extracted feature of each bounding box and the recognized text present within each bounding box, according to a plurality of predefined tags. The system can associate a key with a value and return a key-value pair for each predefined tag.

Abstract: In a method and apparatus for extreme-light image enhancement, an input image is passed to a lighting classification module in order to be classified into two categories: an under-exposed lighting condition and an over-exposed light condition. Then the classified image is subsequently passed to an enhancement module which comprises a first image enhancement unit and a second image enhancement unit using a mapping function based on a gamma mapping function for mapping the classified image to an output image, respectively. A parameter of the gamma mapping function is estimated by a parameter estimation network, based on the classified image. The parameter estimation network may be a lightweight CNN network which is trained by an unsupervised approach.

Abstract: A phase change material (PCM) heat exchanger system for a rocket or other spacecraft is described. The PCM heat exchanger utilizes phase-change material to store heat absorbed from a hot working fluid. The PCM heat exchanger may be configured as an integrated modular double brazed layout that includes folded fins to distribute heat from a working fluid (e.g., hydraulic fluid) to PCM. A modular configuration may enable a heat exchanger system to be scaled up or down by adding or removing modules to meet cooling requirements for particular rockets and their flights.

Abstract: Computer vision systems and methods for text classification are provided. The system detects a plurality of text regions in an image and generates a bounding box for each detected text region. The system utilizes a neural network to recognize text present within each bounding box and classifies the recognized text, based on at least one extracted feature of each bounding box and the recognized text present within each bounding box, according to a plurality of predefined tags. The system can associate a key with a value and return a key-value pair for each predefined tag.

Abstract: The present disclosure describes methods and system for personalizing user experience in a gaming network. In particular, the user experience is personalized based on how users are characterized based on their interactions with the gaming network. By using the characterizations, the users are assigned labels that publicly identify the user experience, interest, and proficiency with various video games. Communities are then established based on users having the same labels. Lastly, user generated content can be characterized and promoted based on the characterizations to the appropriate communities.

Abstract: A tool assembly for mounting a tailgate to a car body is provided. The tool assembly includes a bracket adapted to engage with an overhead structure and a frame movably coupled to the bracket and configured to move in a vertical direction relative to the bracket. The tool assembly also includes a linkage mechanism movably coupling the frame with the bracket and configured to maintain the frame parallel to the bracket during the vertical movement of the frame. Further, a pair of torque guns is coupled to the frame and is configured to hold a pair of fasteners. The pair of torque guns engages and tightens the pair of fasteners to the car body and a hinge attached to the tailgate.

Abstract: Computer vision systems and methods for text classification are provided. The system detects a plurality of text regions in an image and generates a bounding box for each detected text region. The system utilizes a neural network to recognize text present within each bounding box and classifies the recognized text, based on at least one extracted feature of each bounding box and the recognized text present within each bounding box, according to a plurality of predefined tags. The system can associate a key with a value and return a key-value pair for each predefined tag.

Abstract: In an approach to generating conversational image representations, one or more computer processors detect one or more utterances by a user, wherein utterances are either textual or acoustic. The one or more computer processors generate one or more image representations of the one or more detected utterances utilizing a generative adversarial network restricted by one or more user privacy parameters, wherein the generative adversarial network is fed with an extracted sentiment, a generated avatar, an identified topic, an extracted location, and one or more user preferences. The one or more computer processors display the generated one or more image representations on one or more devices associated with respective one or more recipients of the one or more utterances.

Abstract: The present disclosure describes methods and system for personalizing user experience in a gaming network. In particular, the user experience is personalized based on how users are characterized based on their interactions with the gaming network. By using the characterizations, the users are assigned labels that publicly identify the user experience, interest, and proficiency with various video games. Communities are then established based on users having the same labels. Lastly, user generated content can be characterized and promoted based on the characterizations to the appropriate communities.

Abstract: The present disclosure describes methods and system for personalizing user experience in a gaming network. In particular, the user experience is personalized based on how users are characterized based on their interactions with the gaming network. By using the characterizations, the users are assigned labels that publicly identify the user experience, interest, and proficiency with various video games. Communities are then established based on users having the same labels. Lastly, user generated content can be characterized and promoted based on the characterizations to the appropriate communities.

Abstract: A method, computer system, and a computer program product for payload stabilization is provided. The present invention may include, in response to receiving at least one sensor data associated with a suspended payload, detecting an unstable movement in the suspended payload during a transport of the suspended payload. The present invention may also include implementing at least one sail coupled to the suspended payload to stabilize the detected unstable movement of the suspended payload.

Abstract: In a method and apparatus for extreme-light image enhancement, an input image is passed to a lighting classification module in order to be classified into two categories: an under-exposed lighting condition and an over-exposed light condition. Then the classified image is subsequently passed to an enhancement module which comprises a first image enhancement unit and a second image enhancement unit using a mapping function based on a gamma mapping function for mapping the classified image to an output image, respectively. A parameter of the gamma mapping function is estimated by a parameter estimation network, based on the classified image. The parameter estimation network may be a lightweight CNN network which is trained by an unsupervised approach.

Abstract: In some examples, a user, either a customer or potential customer of a business, engages in conversations with a virtual assistant (VA) provided by the business. The virtual assistant (VA) is further supported by one or more human assistants (HA), if needed. In embodiments, to facilitate seamless transitions between a VA and a HA, when needed, an intelligent decision maker (IDM) is provided. The IDM receives a user question and a proposed answer to the question from a VA, evaluates the proposed answer in the context of the conversation, and determines if the proposed answer requires further review by an HA. In response to a determination that the proposed answer requires further review, the IDM sends the proposed answer to an HA, and, in response to an indication by the HA, takes further action in the conversation.

Abstract: Computer vision systems and methods for text classification are provided. The system detects a plurality of text regions in an image and generates a bounding box for each detected text region. The system utilizes a neural network to recognize text present within each bounding box and classifies the recognized text, based on at least one extracted feature of each bounding box and the recognized text present within each bounding box, according to a plurality of predefined tags. The system can associate a key with a value and return a key-value pair for each predefined tag.

Abstract: Techniques regarding action detection based on motion in receptive fields of a neural network model are provided. For example, one or more embodiments described herein can comprise a system, which can comprise a memory that can store computer executable components. The system can also comprise a processor, operably coupled to the memory, and that can execute the computer executable components stored in the memory. The computer executable components can comprise a motion component that can extract a motion vector from a plurality of adaptive receptive fields in a deformable convolution layer of a neural network model. The computer executable components can also comprise an action detection component that can generate a spatio-temporal feature by concatenating the motion vector with a spatial feature extracted from the deformable convolution layer.

Abstract: A computer system, a computer program product, and a computer-implemented system are provided for leveraging a national language processing (NLP) system for dynamically generating natural language output data. A NLP module investigates text or communication data from one or more platforms and derives global characteristic data from the investigated data. The derived global characteristic data is subject to modulation with a captured local writing style corresponding to a captured relationship. Contextual information is dynamically identified. Real-time natural language output communication data is generated that incorporates communication dynamics from the modulated global characteristic data and the dynamically identified contextual information.

Abstract: Location information associated with a parking area is received. Information about a plurality of vehicles parked in the parking area is determined. A first space located between a first parked vehicle and a first non-movable object located in front of the first parked vehicle is determined. The first space is comprised of a first required space and a first non-required space. A second space located between the first parked vehicle and a second non-movable object located behind the first parked vehicle is determined. The second space is comprised of a second required space and a second non-required space. Responsive to determining that the first non-required space is greater than the second non-required space, the first parked vehicle is moved towards the first space. After moving the first parked vehicle, the first space is equivalent to the first required space.

Abstract: In an approach to generating conversational image representations, one or more computer processors detect one or more utterances by a user, wherein utterances are either textual or acoustic. The one or more computer processors generate one or more image representations of the one or more detected utterances utilizing a generative adversarial network restricted by one or more user privacy parameters, wherein the generative adversarial network is fed with an extracted sentiment, a generated avatar, an identified topic, an extracted location, and one or more user preferences. The one or more computer processors display the generated one or more image representations on one or more devices associated with respective one or more recipients of the one or more utterances.

Abstract: A method for providing adaptive vehicle-proximity guidance may include monitoring transit-condition data of a roadway traversed by a user-vehicle. The method may further include determining, based at least in part on the transit-condition data, a proximity zone. The method may further include generating a first visual representation that corresponds to the proximity zone. The method may further include displaying the first visual representation onto the roadway proximate the proximity zone and updating the first visual representation in response to detected changes in the transit-condition data.

Abstract: Aspects of the invention include a computer-implemented method for quantifying tester sentiment. The computer-implemented method includes receiving a first feedback data from a first tester, where the first feedback data represents feedback generated by the first tester in connection with a first instance of a first software-under-development. The first feedback data is correlated to an aspect of the first instance of the first software-under-development to derive a tester sentiment data. The tester sentiment data is used to determine a tester sentiment rating of the first instance of the software-under-development. Based on the tester sentiment rating, a resource is applied to the first instance of the first software-under-development.