WO2023067557 - EFFICIENT VIDEO EXECUTION METHOD AND SYSTEM
National phase entry:
Publication Number
WO/2023/067557
Publication Date
27.04.2023
International Application No.
PCT/IB2022/060116
International Filing Date
21.10.2022
Title **
[English]
EFFICIENT VIDEO EXECUTION METHOD AND SYSTEM
[French]
PROCÉDÉ ET SYSTÈME D'EXÉCUTION DE VIDÉO EFFICACE
Applicants **
SPECTRUM OPTIX INC.
Inventors
GORDON, Kevin
D'AMORE, Colin
PUT, Timothy
Priority Data
63/270,325
21.10.2021
US
Application details
| Total Number of Claims/PCT | * |
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International Searching Authority |
CIPO
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| Recordal of a Change of the Applicant's Name/Address |
Change of Applicant's Name and Address
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| Type of Assignment |
The Standard Agent's Assignment
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| Applicant's Legal Status |
Legal Entity
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| Entry into National Phase under |
Chapter I
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| Patent Delivery |
Send the Letters Patent by Courier
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| Translation |
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* The data is based on automatic recognition. Please verify and amend if necessary.
** IP-Coster compiles data from publicly available sources. If this data includes your personal information, you can contact us to request its removal.
Quotation for National Phase entry
| Country | Stages | Total | |
|---|---|---|---|
| China | Filing, Examination, Granting | 1993 | |
| EPO | Filing, Examination, Granting | 11718 | |
| Japan | Filing, Examination, Granting | 1952 | |
| South Korea | Filing, Examination, Granting | 1664 | |
| USA | Filing, Examination, Granting | 5940 |

Total:
23,267
The term for entry into the National Phase has expired. This quotation is for informational purposes only
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Abstract[English]
An image processing pipeline includes an image processing system having multiple neural networks arranged to receive multiple input images, with the images having identifiable objects and noise features. A first neural network provides image information to a second neural network that recurrently processes the image information to both improve output presentation of identifiable objects and reduce noise features. In some embodiments other local or remote neural networks can be arranged to modify at least one of an image capture setting, sensor processing, global post processing, local post processing, portfolio post processing, or provide latent vectors or neural embedding information.[French]
Un pipeline de traitement d'image comprend un système de traitement d'image présentant de multiples réseaux neuronaux agencés pour recevoir de multiples images d'entrée, les images présentant des objets identifiables et des caractéristiques de bruit. Un premier réseau neuronal fournit des informations d'image à un second réseau neuronal qui traite de façon récurrente les informations d'image pour à la fois améliorer la présentation de sortie d'objets identifiables et réduire les caractéristiques de bruit. Dans certains modes de réalisation, d'autres réseaux neuronaux locaux ou distants peuvent être agencés pour modifier un réglage de capture d'image, et/ou un traitement de capteur, et/ou un post-traitement global, et/ou un post-traitement local, et/ou un post-traitement de portefeuille, ou pour fournir des vecteurs latents ou des informations d'incorporation neuronale.