** ***** ** ********** to ****** ********** ***** offering, **-**-******, *** ** examine ***** ********* ***** related ** **** **** Recognition ***********.
** **** **** ** look **:
- *** ** **********?
- **** ** **********'* **-**-******?
- *** ** **********'* **** Recognition *********?
- *** **** ********** **** NIST **** *******?
- **** ******** **** ***** analytics *** **?
- *** *** **********'* *** partners?
- *** **** ********** ******* to *********?
Paravision ********
******* ** **** ** San *********, ********** ** lead ***** **** ****. ** *** ******* in ** ***** ******* Officer ** ****, *** became *** ** ****. Aley *** * ********** in ******** **** *********, product **********, *** ******** development. ********** ******* **** 40 *********, **** ~**% deep ******** ***********.********** ********* **** ******** **** ** * pivot **** ********-****** ********* to ********** *** ************.
********** **** **** **** raised $** ******* ** funding, **** ******** *$** ******* ****** * round ** ************ ********. ********** **** ***** they *** *** ********* looking ** ***** **** funds, **** *** ****** to ***** ******* ***** of ******* ** *** future.
OEM **** *********** *** ******** ************
********** ** ** *** provider ** ** **** recognition. **** **** **** do *** **** ********** branded ******* ****** ** end-users *** ** **** customized ******* ****** ** some ** ********** ********. Because ** ***** ***** on ********* *** ********, Paravision **** **** **** "flexible ******* **********" ***** on *** ******** **** OEM *****.
*** ** ************* ********, Paravision **** *** ******* a **** ** ***** OEM ********, *******,******** **(****-**-*-********** ****** *******) **** IPVM **** *** ********** face ***********.
Critical *********** *****
********** ********** **** **** developed ***** **** *********** models, ******** ** ******, fast-performing ****** *** *** in **** ***** *******-******** applications.
NIST ********* ********
**********'* ******* ********* ** focused ****** **** *********** ********, ******** ** ** "Global #* **** *** Face ***********". *******, ** many ** *** *********** tests, ********** ** *** #1 (*.*. ******* ****, 2019 ******* ***** **** Paravision ** #* ** 1:1 *******). **** ******** new ******* ************* **** per *****, ** ***** results, *** *** ********** will ****** **********.
************, **** ** ******** perspective, *** *** ** results *** ****** ******-***** percentages ** **** *****
********** **** **** **** the ********* **** ***** at *** *** ** the **** ***** ********* stay ***** ****** **** stop ********** *** *******, and **** ***** ** NIST ******* ** * way ** *** ** a ******* ********* **** potential *** ********. **** also **** ***** ******** "across *** **** ***** of *****" ** ***** goal, *** ********, ****** that **** * ********* have ****** ** *** top ** ****** *** NIST *****: **********,**********, *******.
NIST ********* ***********
********** **** **** **** send ***** ************ ********* algorithms ** ****, *** said **** ***** ** their **** ******* (** competitive *******, ****** *****, and ******** ****) **** suspect **** ******* *** submitting ***-********** **********. ***-********** analytics *** **** ********** neural ******* ****** ***** require **** ********** *** decreased *****, *** ****** in ****** ******** **** commercially ********* ******.
************, **** **** ***** NIST **** * **** job ** * *********, algorithms **** ******* ** 99% ** **** ***** will ***** ~**% ** production. ******* ********* ** their *******, **** ** much ****** **** ***** public ******** (*.*.********,***** ** *** ****), ***** *** ****** in * **% ******** in *******, *** **% accuracy ** **********.
Cybersecurity ******* *****
***** ****** ***** **** recognition ** ***** ** industry-standard ********** (*.*.**********,********), **** ***** *** share ******* ***** *** neural ******* ************ ** training *******, ****** ************* concerns. **** ********* **** they ** *** *** publically ********* ********, ***** is *** ****** ** the ** ***** ********* market, *** **** **** only *** ******* ******** with ***** ***-** ****** for ********.
********** ******* ** ******** about********** *********** ******* ********* ******** **** ** analytics (*********, ******, *****), and ***** **** ********-**-********* is *** ******* **** use ** ******* ***** analytics *** ********, *** is **** *** **** do *** ***** ***** partner ****.
**** *** *** ******** any ********** ********* ******* that ***** **** ***** system **** ****** ** be ***********. ********** * person ******* ** ****** Paravision ***** ****** * partner's ****** ** *** field ** ********.
Broad ******** *******
********** **** **** *** the **** *********** ****** in *** ******** ************* (e.g. ***, ***, *** Power **** *******) ***** noting **** ***** ***** be **** ******** ** processing **** ********* ** the ********** ** *** hardware ********. **** **** their **** *********** ***** be ** ******** ** a ******** ******* ** quadcore *** ** * high-powered ****** ***. **** has *** ****** ********** face ***********.
**** ***** **** ** one ** *** ******* differentiators ******* ***** **** recognition *** ***** ***** commercial ********* (*********, ******), which *** *** **** to ** ********* ** on-premise ********** ** ******** in *******.
Engineering *****
********** ********** **** ********** top ********* *** ******* those ********* ******* ** AI/Neural ******* ******** ** the ******* ***** ***** ******* ****, *** *** * background ******** ******** *********** at ******, ********, *** multiple ******* ****** ********. They ***** **** *** enabled **** ** **** a **** *********** *********** team ** ** ******* learning ********* **** * PhDs.
**** **** ***** **** focuses ** *************** **** neural ******* ***************, ***** size *** ***********, *** the ********* ***********/************* ******** with ********* ******** *********.
Compared ** *********
********* *** ********** **** opposing **-**-****** **********. ********** sells ** *** ******** and ***** ******** ** to *** *******, ***** Anyvision ******** (*** ****)* **** ****** ** security ******** *********** ***** directly ********* ********** *********. Additionally, ********* *** ** end-user ******** ********* **** minimal ************, ***** ********** is ********* ********* * face *********** ******** *** OEM ******** ** ***** into ***** *** ********.
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