Abstract: Aspects of the subject disclosure may include, for example, identifying a first location of an antenna, causing a first ray to be emitted from a second location that is different from the first location, generating reflected surfaces from surfaces that the first ray reflects from, generating a reflected first location of the first location using the surfaces that the first ray reflects from, identifying, based on the reflected first location, potential locations along the surfaces that the first ray reflects from using the reflected surfaces, and verifying, based on the potential locations, that the first ray traverses a valid path between the first location and the second location. Other embodiments are disclosed.

Abstract: Aspects of the subject disclosure may include, for example, a method of: gathering, by a processing system including a processor, network data comprising a plurality of data modalities, wherein the data modalities include numerical data, tabular data, time series data, and event sequence data; pre-training, by the processing system, a generative artificial intelligence (AI) using the network data; fine-tuning, by the processing system, the generative AI to create a specific downstream application; and applying, by the processing system, the specific downstream application to generate a recommendation for a user. Other embodiments are disclosed.

Abstract: Aspects of the subject disclosure may include, for example, identifying a first location of an antenna, causing a first ray to be emitted from a second location that is different from the first location, generating reflected surfaces from surfaces that the first ray reflects from, generating a reflected first location of the first location using the surfaces that the first ray reflects from, identifying, based on the reflected first location, potential locations along the surfaces that the first ray reflects from using the reflected surfaces, and verifying, based on the potential locations, that the first ray traverses a valid path between the first location and the second location. Other embodiments are disclosed.

Abstract: In one example, a method performed by a processing system including at least one processor includes creating a geospatial model of an environment in which a cellular network is to be deployed, transforming, for each cellular antenna of a proposed antenna layout of the cellular network, a radiation pattern of the each cellular antenna into a signal strength array, to create a plurality of signal strength arrays, augmenting, for each signal strength array of the plurality of signal strength arrays, the each signal strength array with at least one parameter of a corresponding cellular antenna of the proposed antenna layout and at least one value describing the environment in which the cellular network is to be deployed, and estimating a coverage of the proposed antenna layout based on the signal strength array, as augmented, using a machine learning model.

Abstract: In one example, a method performed by a processing system including at least one processor includes creating a geospatial model of an environment in which a cellular network is to be deployed, transforming, for each cellular antenna of a proposed antenna layout of the cellular network, a radiation pattern of the each cellular antenna into a signal strength array, to create a plurality of signal strength arrays, augmenting, for each signal strength array of the plurality of signal strength arrays, the each signal strength array with at least one parameter of a corresponding cellular antenna of the proposed antenna layout and at least one value describing the environment in which the cellular network is to be deployed, and estimating a coverage of the proposed antenna layout based on the signal strength array, as augmented, using a machine learning model.

Abstract: Aspects of the subject disclosure may include, for example, obtaining a plurality of inputs, wherein the plurality of inputs includes a first image captured by a first camera at a first point in time, processing the plurality of inputs to generate a first prediction regarding a first characteristic of a first signal associated with a first vehicle that is to be detected by a receiver at a second point in time that is subsequent to the first point in time, and modifying, based on the first prediction, a first parameter of a transmitter that emits the first signal, a second parameter of the receiver, or a combination thereof. Other embodiments are disclosed.

Abstract: In one example, a method performed by a processing system including at least one processor includes creating a geospatial model of an environment in which a cellular network is to be deployed, transforming, for each cellular antenna of a proposed antenna layout of the cellular network, a radiation pattern of the each cellular antenna into a signal strength array, to create a plurality of signal strength arrays, augmenting, for each signal strength array of the plurality of signal strength arrays, the each signal strength array with at least one parameter of a corresponding cellular antenna of the proposed antenna layout and at least one value describing the environment in which the cellular network is to be deployed, and estimating a coverage of the proposed antenna layout based on the signal strength array, as augmented, using a machine learning model.

Abstract: Aspects of the subject disclosure may include, for example, identifying a first location of an antenna, causing a first ray to be emitted from a second location that is different from the first location, generating reflected surfaces from surfaces that the first ray reflects from, generating a reflected first location of the first location using the surfaces that the first ray reflects from, identifying, based on the reflected first location, potential locations along the surfaces that the first ray reflects from using the reflected surfaces, and verifying, based on the potential locations, that the first ray traverses a valid path between the first location and the second location. Other embodiments are disclosed.

Abstract: A system for dynamic derivation of and sending to a contact group. The system may recognize an emergency situation (natural disaster, stranded, lost cell connection) and send a confirmation that may be sent to different contact groups from a network entity. The system may also recognize anomalous user behaviors and send a message indicating the anomalous user behaviors to different contact groups from the network entity.

Abstract: A system for dynamic derivation of and sending to a contact group. The system may recognize an emergency situation (natural disaster, stranded, lost cell connection) and send a confirmation that may be sent to different contact groups from a network entity. The system may also recognize anomalous user behaviors and send a message indicating the anomalous user behaviors to different contact groups from the network entity.

Abstract: A system for dynamic derivation of and sending to a contact group. The system may recognize an emergency situation (natural disaster, stranded, lost cell connection) and send a confirmation that may be sent to different contact groups from a network entity.

Abstract: A system for dynamic derivation of and sending to a contact group. The system may recognize an emergency situation (natural disaster, stranded, lost cell connection) and send a confirmation that may be sent to different contact groups from a network entity.

Abstract: A method of increasing resolution of an image includes generating vector contours associated with a first image and scaling the vector contours to a second resolution. The first image has a first resolution, and the second resolution is greater than the first resolution. The vector contours are rendered to generate a guiding image at the second resolution, and a second image is generated from the first image based on the guiding image, by using joint upsampling. The second image is generated at the second resolution. The vector contours can be generated by bitmap tracing binary images at different quantization levels. An apparatus and computer readable device implementing the method of increasing the resolution of an image are also provided.

Abstract: A method of increasing resolution of an image includes generating vector contours associated with a first image and scaling the vector contours to a second resolution. The first image has a first resolution, and the second resolution is greater than the first resolution. The vector contours are rendered to generate a guiding image at the second resolution, and a second image is generated from the first image based on the guiding image, by using joint upsampling. The second image is generated at the second resolution. The vector contours can be generated by bitmap tracing binary images at different quantization levels. An apparatus and computer readable device implementing the method of increasing the resolution of an image are also provided.

Abstract: A method of increasing resolution of an image includes generating vector contours associated with a first image and scaling the vector contours to a second resolution. The first image has a first resolution, and the second resolution is greater than the first resolution. The vector contours are rendered to generate a guiding image at the second resolution, and a second image is generated from the first image based on the guiding image, by using joint upsampling. The second image is generated at the second resolution. The vector contours can be generated by bitmap tracing binary images at different quantization levels. An apparatus and computer readable device implementing the method of increasing the resolution of an image are also provided.

Abstract: A method of increasing resolution of an image includes generating vector contours associated with a first image and scaling the vector contours to a second resolution. The first image has a first resolution, and the second resolution is greater than the first resolution. The vector contours are rendered to generate a guiding image at the second resolution, and a second image is generated from the first image based on the guiding image, by using joint upsampling. The second image is generated at the second resolution. The vector contours can be generated by bitmap tracing binary images at different quantization levels. An apparatus and computer readable device implementing the method of increasing the resolution of an image are also provided.

Abstract: A method of increasing resolution of an image includes generating vector contours associated with a first image and scaling the vector contours to a second resolution. The first image has a first resolution, and the second resolution is greater than the first resolution. The vector contours are rendered to generate a guiding image at the second resolution, and a second image is generated from the first image based on the guiding image, by using joint upsampling. The second image is generated at the second resolution. The vector contours can be generated by bitmap tracing binary images at different quantization levels. An apparatus and computer readable device implementing the method of increasing the resolution of an image are also provided.

Abstract: A method of increasing resolution of an image includes generating vector contours associated with a first image and scaling the vector contours to a second resolution. The first image has a first resolution, and the second resolution is greater than the first resolution. The vector contours are rendered to generate a guiding image at the second resolution, and a second image is generated from the first image based on the guiding image, by using joint upsampling. The second image is generated at the second resolution. The vector contours can be generated by bitmap tracing binary images at different quantization levels. An apparatus and computer readable device implementing the method of increasing the resolution of an image are also provided.

Abstract: A method of increasing resolution of an image includes generating vector contours associated with a first image and scaling the vector contours to a second resolution. The first image has a first resolution, and the second resolution is greater than the first resolution. The vector contours are rendered to generate a guiding image at the second resolution, and a second image is generated from the first image based on the guiding image, by using joint upsampling. The second image is generated at the second resolution. The vector contours can be generated by bitmap tracing binary images at different quantization levels. An apparatus and computer readable device implementing the method of increasing the resolution of an image are also provided.

Abstract: A method of increasing resolution of an image includes generating vector contours associated with a first image and scaling the vector contours to a second resolution. The first image has a first resolution, and the second resolution is greater than the first resolution. The vector contours are rendered to generate a guiding image at the second resolution, and a second image is generated from the first image based on the guiding image, by using joint upsampling. The second image is generated at the second resolution. The vector contours can be generated by bitmap tracing binary images at different quantization levels. An apparatus and computer readable device implementing the method of increasing the resolution of an image are also provided.