# US 2019/0171916 A1 · Increasing network transmission capacity and data resolution quality and computer systems and computer-implemented methods for implementing thereof

> Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt

- Number: US 2019/0171916 A1
- Document ID: US20190171916A1
- Status: Published application
- Kind: A1
- Application number: 16/199,844
- Filed: 2018-11-26
- Published: 2019-06-06
- Earliest claimed: 2017-05-23
- Assignees: Banuba Limited
- Applicants: Banuba Limited
- Inventors: Viktor Prokopenya; Yury Hushchyn; Alexander Lemeza
- Web page: https://patentgrep.com/patent/US20190171916A1

## CPC

- G06V 10/82: using neural networks
- G06F 18/24: Classification techniques
- G06F 18/24133: {Distances to prototypes}
- G06F 18/285: {Selection of pattern recognition techniques, e.g. of classifiers in a multi-classifier system}
- G06N 3/045: Combinations of networks
- G06N 3/0464: Convolutional networks [CNN, ConvNet]
- G06N 3/08: Learning methods
- G06N 3/09: Supervised learning
- G06V 10/454: {Integrating the filters into a hierarchical structure, e.g. convolutional neural networks [CNN]}
- G06V 10/87: {using selection of the recognition techniques, e.g. of a classifier in a multiple classifier system}
- G06V 30/19173: {Classification techniques}
- G06V 40/10: Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands
- G06V: IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06F: ELECTRIC DIGITAL DATA PROCESSING (computer systems based on specific computational models G06N)
- G06N: COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS

## Abstract

In some embodiments, the present invention provides for an exemplary inventive system, icluding: a communication pipeline, including: at a first end of the communication pipeline: a first processor configured to: obtain a plurality of original content data units having a representative content associated with a subject; apply a trained artificial intelligence algorithm to identify: the representative content of the subject and original background content that is not associated with the subject; remove the original background content to reduce a volume of data being transmitted resulting in an increased capacity of the communication channel; encode and transmit each respective modified content data unit from the first end of the communication pipeline to a second end; a second processor configured to: receive and decode each respective modified content data unit; generate a respective artificial background content; and combine the representative content associated with the subject and the respective artificial background content to form each composite content data unit.

## Claims

### Claim 1

A computer-implemented method, comprising:
obtaining, by at least one first processor, a plurality of original content data units having a representative content associated with at least one subject;
encoding, by the at least one first processor, each respective original content data unit in accordance with at least one data encoding-decoding methodology; and
transmitting, by the at least one first processor, each respective encoded original content data unit to a destination.