#AI / #Health #Stock News: GBT Tokenize
(OTCPINK: $GTCH) Is Developing Real Time Object Detection Algorithms And
Techniques For Kirlian Research; #Artificialintelligence
SAN DIEGO - February 23, 2021 (Investorideas.com Newswire) GBT Technologies Inc. (OTCPINK: GTCH) ("GBT", or the "Company"), together with GBT Tokenize Corp ("GBT/Tokenize") is developing real time algorithms and techniques for Kirlian research. A Kirilian image includes vast amount of graphical data. GBT/Tokenize research is aiming to develop a system and method to analyze this data as a potential of health-related information source. These algorithms and methods are pattern detection and recognition, based on unique principles. An image's objects are categorized according to their physical characteristics like shape, color, texture, and more. A machine learning based flow is targeted to operate as an object's classifier and analytics processor. We believe that the object detection and analytics method can be used for processing Kirlian images for their characteristics as another stage of GBT/Tokenize's Kirlian Electrophotography research.
Read this news, featuring GTCH in full at https://www.investorideas.com/CO/GOPH/news/2021/02231Kirlian-Research.asp
Kirlian photography method introduces a series of
techniques that are based on the phenomenon known as electrical coronal
discharge. This technique produces an object's energy related images with a
colorful representation called aura. When performed on human organs, although
not scientifically proven, some believe that these images can be interpreted to
analyze health conditions. GBT/Tokenize is researching the development of
imaging related techniques to further investigate the data generated from these
images for possible health related conclusions. The research is not medical but
technical and targeted to conclude a real time analysis of Kirilian images that
may be related to human's health conditions.
Kirlian Research Rendering Analysis sample
GBT Tokenize Is Developing Real Time Object
Detection Algorithms And Techniques For Kirlian Research
The goal of our research is to enable a machine
learning algorithm to decide as to whether an image's object is of interest or
not, pointing a possible health related conclusion. A Kirlian image contains a
huge amount of data. The detection and analytics of a Kirlian image requires
major computational capabilities in a real time operation. A neural network
analysis is done to ensure a reliable object's classification and to train for
the detection of objects of interest within a Kirlian image. The approach
performs an image based color-based pre-processing, to reach a conclusion about
certain pattern and color presented in the image. The goal is to reach a
real-time Kirilian image processing with the use of deep learning algorithms
and supporting computational hardware resources, achieving advanced imaging
conclusions that may provide health related information.
Since a Kirlian image includes a vast amount of
information, a private, custom real-time algorithms is planned to be developed.
This approach is planned to utilize the analysis of an image object's
neighboring positions, utilizing this data to increase the overall detection
speed. The method is contemplated to process a computation of the original
objects and their neighboring information to formulate an efficient flow that
can be repeatedly executed, achieving a true real-time processing. Finally,
advanced algorithmic and hardware related architectures will exploit parallel
processing to accelerate the complex computations operations. Data parallelism
can be achieved using a CPU that performs programmatic instruction, which is
efficient to accelerate large amount of data processing. The company targets
this development to achieve a high speed, real time Kirilian imaging processing
that may be of use for health-related advice.
"As we continue with the Kirlian Imaging
research, we encountered the need for a fast processing of a Kirlian image. A
Kirlian image contains a huge amount of data to be analyzed, especially if we
are interested in a real time processing. An image that is produced by Kirlian
technique includes a colorful, object's energy representation, called Aura. We
are aiming to analyze this Aura, using computational geometry algorithms and
neural network algorithms. Each image's Aura is targeted to be analyzed
according to its color, size, shape and pattern. This type of processing may
take a long time even with advanced computational geometry approaches. Due to
the vast amount of image's data, we are in the need to develop advanced pattern
recognition algorithms that will enable real-time results. We are researching a
new detection and analysis approach to categorize each image's Aura
characteristics and features. The method will analyze geometrical objects,
their relation to their neighbored objects and to the overall image. Each
object will be processed through a module, which we call a classifier to
catalog it within similar set of objects. It is our goal to have a neural network-based
algorithm performing a parallel processing per objects group to achieve rapid,
real-time results. In order to further enhance this processing, we will
consider parallel processing of the data by software and supporting hardware,
i.e. CPUs, GPUs. We are going to invest significant efforts to develop
real-time object detection and pattern recognition methods to reach our goal,
which is a speed lightning, real time analysis. This stage of the research is
aimed to assist with providing the data on-the-fly, possibly advising into
health-related information can be identify underline conditions and
symptoms" stated Danny Rittman, the Company's CTO.
There is no guarantee that the Company will be
successful in researching, developing or implementing this technology. In order
to successfully implement this technology, the Company will need to raise
adequate capital to support its research and, if successfully researched,
developed and granted regulatory approval, the Company would need to enter into
a strategic relationship with a third party that has experience in
manufacturing, selling and distributing this product. There is no guarantee
that the Company will be successful in any or all of these critical steps.
Kirlian Research Rendering Analysis sample:
A photo accompanying this announcement is available
at: https://www.globenewswire.com/NewsRoom/AttachmentNg/51a2a5ea-ea62-425b-b8bc-fd5541f12c4c
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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