#AI #Health #Stock News: GBT Tokenize (OTCPINK: $GTCH) is Developing Advanced Computational Geometry Methods
San Diego, CA, January 5, 2021 – (Investorideas.com Newswire) GBT Technologies Inc. (OTCPINK: GTCH) ("GBT”, or the “Company”), announced that GBT Tokenize (“GBT/Tokenize) is developing new methods for health analysis based on its Kirlian Electrophotography research. GBT/Toeknize is developing a set of methods and algorithms to analyze imaging made by Kirlian Electrophotography.
Read this news, featuring GTCH in full at https://www.investorideas.com/CO/GOPH/news/2021/01051Computational-Geometry-Methods.asp
Kirlian photography
introduces a series of techniques that are based on the phenomenon known as
electrical coronal discharge. Images that are produced using these techniques
present a colorful so-called aura. Although not scientifically proven, some
believe that these images can be interpreted to analyze health conditions.
GBT/Tokenize reiterates that the claim that a medical conclusion can be reached
based on analysis of the image (whether through AI or in person) has not been
scientifically established. GBT/Tokenize is performing open research from a
technological point of view, which cannot be considered medical research or
portrayed to be as such.
It is believed by some
that the Kirlian imaging process is made by placing an object on a photographic
plate that is connected to a source of high-voltage current. A more modern way
is using low voltage hand and head sensors to produce visual, interactive data
that may represent health energy information. Kirlian imaging can produce
organs energetic visualization such as graphical protuberances, halos, and
discharge patterns, which can be analyzed by computer program to identify
unique patterns. GBT is now developing a set of computational geometry
algorithms targeted to be the base for a further AI analysis. Computational
geometry is a mathematical field that involves the design, analysis and
implementation of efficient algorithms for solving geometric problems. Advanced
applications that typically use computational geometry methods are pattern
recognition, computer vision, animation and graphics, (CAD) computer-aided
design, robotics, and similar especially when require real-time speeds. We are
developing a private, derived set of algorithms in order to classify the
combinatorial and numerical computational geometry of Kirlian images. Each set
is designed to identify, analyze and categorize images according to its
parametric surfaces and curves, for example, spline curves and Bezier curves.
This information will be fed to a machine learning program. Our algorithms are
identifying and evaluating the image's surfaces and parts of surfaces from
particular viewing angles in order to categorize and classify anomalies.
"Kirlian imaging of
living tissue may exhibit energy levels that can be visualized as auras. We are
now developing a set of geometrical computation methods and algorithms to
graphically analyze these images further feeding the data into our machine
learning programs. The target is to reach consistent and reliable conclusions
with respect to the analysis of the image and any anomalies. Computational geometry is a field of computer
science that is aimed to solve problems stated in terms of geometry. Here we
are implementing these techniques for Kirilian images to find unique patterns.
The development of these geometrical algorithms is part of our image processing
long term plan and will be further used during next year for AI imaging
analytics. For example, we develop a specific version of Scanline method which
is an algorithm that typically works on a row-by-row basis rather
pixel-by-pixel basis. We created a new flow to identify critical vertexes only
and then analyze pixel-by-pixel. This enables light speed image analysis in
order to search and classify image's points of interest. The main advantage of
our version is that the sorting of crucial vertices only, is done in parallel
with the normal scan, significantly shortening the overall scan time and
reducing objects-of-interest detection time. We develop plane sweep based
algorithms that works via a conceptual sweep line to analyze Kirilian images as
an infrastructure for our AI program. The main idea is to scan across the
image, stopping at object of interest vertexes (points) to identify patterns
and consistencies. These geometric operations will become geometric objects
that will intersect with others to form a human organ aura. By looking for full
and partial similarities, repetitions, or atypical auras patterns, our goal is
to be able to detect dynamic images changes in time. In addition, another set
of computational geometry algorithms will search object's boundaries in order
to detect specific patterns and finding images correlations. The geometrical
computation engine will be the first step to extract the base data from the
Kirilian images and later processed by the AI engine. "
About Us
GBT Technologies, Inc. (OTC PINK: GTCH) (“GBT”) (http://gbtti.com) is a development stage
company which considers itself a native of Internet of Things (IoT), Artificial
Intelligence (AI) and Enabled Mobile Technology Platforms used to increase IC
performance. GBT has assembled a team with extensive technology expertise and
is building an intellectual property portfolio consisting of many patents.
GBT’s mission, to license the technology and IP to synergetic partners in the
areas of hardware and software. Once commercialized, it is GBT’s goal to have a
suite of products including smart microchips, AI, encryption, Blockchain, IC
design, mobile security applications, database management protocols, with
tracking and supporting cloud software (without the need for GPS). GBT
envisions this system as a creation of a global mesh network using advanced
nodes and super performing new generation IC technology. The core of the system
will be its advanced microchip technology; technology that can be installed in
any mobile or fixed device worldwide. GBT’s vision is to produce this system as
a low cost, secure, private-mesh-network between any and all enabled devices.
Thus, providing shared processing, advanced mobile database management and
sharing while using these enhanced mobile features as an alternative to
traditional carrier services.
Forward-Looking Statements
Certain statements contained in this
press release may constitute "forward-looking statements".
Forward-looking statements provide current expectations of future events based
on certain assumptions and include any statement that does not directly relate to any historical or current fact. Actual results
may differ materially from those indicated by such forward-looking statements
as a result of various important factors as disclosed in our filings with the
Securities and Exchange Commission located at their
website ( http://www.sec.gov). In addition to these factors,
actual future performance, outcomes, and results may differ materially because
of more general factors including (without limitation) general industry and market conditions and growth rates, economic
conditions, governmental and public policy changes, the Company’s ability to
raise capital on acceptable terms, if at all, the Company’s successful
development of its products and the integration into
its existing products and the commercial acceptance of the Company’s
products. The forward-looking statements included in this press release
represent the Company's views as of the date of this press release and these
views could change. However, while the Company
may elect to update these forward-looking statements at some point in the
future, the Company specifically disclaims any obligation to do so. These
forward-looking statements should not be relied upon as representing the Company's
views as of any date subsequent to the date of the
press release.
Contact:
Dr. Danny Rittman, CTO
press@gopherprotocol.com
GBT Technologies
Inc. (OTCQB:GTCH) is a featured tech stock on
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