Abstract: A device may receive dynamic customer data and static customer data, and may calculate additional customer data based on the dynamic customer data and the static customer data. The device may process the static customer data, the dynamic customer data, and the additional customer data, with a first machine learning model, to determine a next action prediction, and may process the static customer data, the dynamic customer data, and the additional customer data, with a second machine learning model, to determine a next sequence prediction. The device may concatenate the static customer data, the dynamic customer data, the additional customer data, the next action prediction, and the next sequence prediction to generate concatenated data, and may process the concatenated data, with a plurality of machine learning models, to calculate various outputs, and may generate a recommendation for the customer based on the various outputs.

Abstract: In some implementations, a transcription system may generate a first transcript based on audio data of a conversation between a first user and a second user. The transcription system may determine, using a first machine learning model of the transcript system, that a portion of the first transcript is incorrect. The transcription system may generate, using a second machine learning model, additional data for transcribing the audio data based on determining that the portion of the first transcript is incorrect. The additional data is generated using a portion of the audio data corresponding to the portion of the first transcript. The transcription system may generate a second transcript based on the audio data and the additional data. The transcription system may provide the second transcript to one or more devices.

Abstract: Disclosed are systems and methods for an anomaly detection framework that operates as an executable analysis tool for devices to operate in order to determine whether the device contains an unresponsive touch screen (e.g., defective or malfunctioning touch screen). The disclosed framework can analyze the capacitance capabilities of the touch screen, inclusive of the touch layers associated with the touch screen panel, and determine when a device's touch screen is unresponsive to user provided input, which can be any type of touch or gesture provided on a touch screen.

Abstract: Techniques for identifying and tracking objects in digital content are disclosed. In one embodiment, a method is disclosed comprising obtaining a frame of digital content, the frame comprising pixel data, detecting an object using the pixel data, determining a set of attributes for the detected object, the set of attributes comprising position, object segment and affine attributes, determining a similarity measurement for the detected object and a second object using the set of attributes corresponding to the detected object and the second object's set of attributes, and using the similarity measurement to make a similarity determination whether or not the detected object and the second object are a same object.

Abstract: In an example, a text message sent by a first user equipment (UE) and addressed to a second UE is received. In response to receiving the text message, a set of information associated with the text message is determined based upon information determined by a first carrier of the first UE and/or the second UE. The text message is classified as spam or not spam based upon the set of information.

Abstract: A device may generate first scores for sentences of text based on a cumulative frequency of words in each sentence, may generate second scores for the sentences based on a cumulative frequency of domain entities in each sentence, and may generate third scores for the sentences based on a sentiment analysis of each sentence. The device may generate a summary of the text, may filter the sentences to extract a first set of sentences, may filter the sentences to extract a second set of sentences, and may filter the sentences to extract a third set of sentences. The device may identify and assign weights to a first group of sentences, a second group of sentences, and a third group of sentences, may generate a ranked list of sentences based on the weighted first group, second group, and third group, and may perform actions based on the final summary.

Abstract: The present subject matter provides various technical solutions to technical problems facing automated solutions in building energy audit applications. These solutions leverage heat loss quantification to improve a building's thermal performance and improve or optimize its energy usage. The technical solutions described herein provide various advantages. These solutions include application of deep-learning methods to segment large thermal imagery data sets from a drone. The technical solutions described herein provide improved building thermal efficiency determination using multiple stages of computations to quantify the heat loss for a building envelope.

Abstract: In an example, based upon a first image of a face of a first person, a plurality of augmented images may be generated. Based upon the first image and the plurality of augmented images, a first set of facial feature representations may be generated. A second image comprising a representation of a face of a second person may be identified. A second facial feature representation may be generated based upon the second image. It may be determined, based upon the second facial feature representation and the first set of facial feature representations, that the second person is the first person.

Abstract: A system described herein may provide a technique for identifying states associated with service providers based on biometric, sensor, and/or other information associated with a set of service providers. A request for service may be received, and a particular service provider may be selected based on a particular state associated with the particular service provider, as determined based on the biometric, sensor, and/or other information associated with the particular service provider. State information associated with a requestor of the service may be identified and used as a factor in selecting the particular service provider to respond to the service request.

Abstract: A device may receive unprocessed images to be labeled, and may utilize a first neural network model to identify objects of interest in the unprocessed images and bounding boxes for the objects of interest. The device may annotate the objects of interest to generate annotated objects of interest, and may utilize a second neural network model to group the annotated objects of interest into clusters. The device may utilize a third neural network model to determine labels for the clusters, and may request manually-generated labels for clusters for which labels are not determined. The device may receive the manually-generated labels, and may label the unprocessed images with the labels and the manually-generated labels to generate labeled images. The device may generate a training dataset based on the labeled images, and may train a computer vision model with the training dataset to generate a trained computer vision model.

Abstract: One or more computing devices, systems, and/or methods for determining an intention of a message and/or performing one or more operations based upon the intention are provided. In an example, a first set of text may be received, from a client device, via a messaging interface. Based upon the first set of text, one or more sets of text semantically similar to the first set of text may be determined. Based upon the first set of text and the one or more sets of text a plurality of intention predictions may be determined. A first intention of the first set of text may be determined based upon the plurality of intention predictions. One or more operations may be performed based upon the first intention.

Abstract: Systems and methods described herein utilize synthetic pixel generation using a custom neural network to generate synthetic versions of objects hidden by occlusions for effective detection and tracking. A computing device stores an object detector model and a synthetic image generator model; receives a video feed; detects objects of interest in a current frame of the video feed; identifies an occluded object in the current frame; retrieves a previous frame from the video feed; generates synthetic data based on the previous frame for the occluded object; and forwards a modified version of the current frame to an object tracking system, wherein the modified version of the current frame includes the synthetic data.

Abstract: The present subject matter provides various technical solutions to technical problems facing automated solutions in building energy audit applications. These solutions leverage heat loss quantification to improve a building's thermal performance and improve or optimize its energy usage. The technical solutions described herein provide various advantages. These solutions include application of deep-learning methods to segment large thermal imagery data sets from a drone. The technical solutions described herein provide improved building thermal efficiency determination using multiple stages of computations to quantify the heat loss for a building envelope.

Abstract: One or more computing devices, systems, and/or methods are provided. In an example, a conversation path associated with a revised code segment of a conversational interaction entity is identified by a processor. The conversation path has a predetermined intent. A conversational phrase is generated by the processor for the conversation path. The conversational interaction entity is employed by the processor using the conversation path and the conversational phrase to generate a resultant intent. An issue report is generated by the processor for the conversational interaction entity responsive to the resultant intent not matching the predetermined intent.

Abstract: A system described herein may provide a technique for identifying states associated with service providers based on biometric, sensor, and/or other information associated with a set of service providers. A request for service may be received, and a particular service provider may be selected based on a particular state associated with the particular service provider, as determined based on the biometric, sensor, and/or other information associated with the particular service provider. State information associated with a requestor of the service may be identified and used as a factor in selecting the particular service provider to respond to the service request.

Abstract: Apparatus and methods performing secure communications in an energy delivery system. Energy delivery systems may include phasor measurement units (PMU), phasor data concentrators (PDC) along with power generation, transmission and consumption equipment. The PMU and PDC may communicate in a grid network over secured wired or wireless communication protocols. Embodiments may include utilizing spread spectrum communication between PMU devices and PDC devices to sustain energy delivery functionality during a communications attack. Communications security may include a cryptographic key management scheme for secure PMU and PDC communication and identification. Embodiments may include clustering of PMU and PDC data for analysis and real-time presentation to grid operators. Embodiments may include clustering of PMU devices in a hexagonal geometry to provide for frequency reuse among devices with directional antenna.

Abstract: Apparatus and methods performing secure communications in an energy delivery system. Energy delivery systems may include phasor measurement units (PMU), phasor data concentrators (PDC) along with power generation, transmission and consumption equipment. The PMU and PDC may communicate in a grid network over secured wired or wireless communication protocols. Embodiments may include utilizing spread spectrum communication between PMU devices and PDC devices to sustain energy delivery functionality during a communications attack. Communications security may include a cryptographic key management scheme for secure PMU and PDC communication and identification. Embodiments may include clustering of PMU and PDC data for analysis and real-time presentation to grid operators. Embodiments may include clustering of PMU devices in a hexagonal geometry to provide for frequency reuse among devices with directional antenna.

Abstract: Any computer process has the opportunity of attempting to load a data object into a global shared library area and, in the event that there is insufficient space in this global area resulting in a failure to load, there is then an automatic location or creation of a named shared library area for the data object that is transparent and does not need and user action.