View source for Huawei technologies co., ltd. (20240161488). INDEPENDENT POSITIONING OF AUXILIARY INFORMATION IN NEURAL NETWORK BASED PICTURE PROCESSING simplified abstract

=INDEPENDENT POSITIONING OF AUXILIARY INFORMATION IN NEURAL NETWORK BASED PICTURE PROCESSING=


==Organization Name==

[[:Category:huawei technologies co., ltd.|huawei technologies co., ltd.]]


[[Category:huawei technologies co., ltd.]]

==Inventor(s)==

[[:Category:Timofey Mikhailovich Solovyev of Munich (DE)|Timofey Mikhailovich Solovyev of Munich (DE)]][[Category:Timofey Mikhailovich Solovyev of Munich (DE)]]

[[:Category:Elena Alexandrovna Alshina of Munich (DE)|Elena Alexandrovna Alshina of Munich (DE)]][[Category:Elena Alexandrovna Alshina of Munich (DE)]]

[[:Category:Biao Wang of Shenzhen (CN)|Biao Wang of Shenzhen (CN)]][[Category:Biao Wang of Shenzhen (CN)]]

[[:Category:Alexander Alexandrovich Karabutov of Munich (DE)|Alexander Alexandrovich Karabutov of Munich (DE)]][[Category:Alexander Alexandrovich Karabutov of Munich (DE)]]

[[:Category:Mikhail Vyacheslavovich Sosulnikov of Munich (DE)|Mikhail Vyacheslavovich Sosulnikov of Munich (DE)]][[Category:Mikhail Vyacheslavovich Sosulnikov of Munich (DE)]]

[[:Category:Georgy Petrovich Gaikov of Munich (DE)|Georgy Petrovich Gaikov of Munich (DE)]][[Category:Georgy Petrovich Gaikov of Munich (DE)]]

[[:Category:Han Gao of Shenzhen (CN)|Han Gao of Shenzhen (CN)]][[Category:Han Gao of Shenzhen (CN)]]

[[:Category:Panqi Jia of Munich (DE)|Panqi Jia of Munich (DE)]][[Category:Panqi Jia of Munich (DE)]]

[[:Category:Esin Koyuncu of Munich (DE)|Esin Koyuncu of Munich (DE)]][[Category:Esin Koyuncu of Munich (DE)]]

[[:Category:Sergey Yurievich Ikonin of Moscow (RU)|Sergey Yurievich Ikonin of Moscow (RU)]][[Category:Sergey Yurievich Ikonin of Moscow (RU)]]

[[:Category:Semih Esenlik of Munich (DE)|Semih Esenlik of Munich (DE)]][[Category:Semih Esenlik of Munich (DE)]]

==INDEPENDENT POSITIONING OF AUXILIARY INFORMATION IN NEURAL NETWORK BASED PICTURE PROCESSING - A simplified explanation of the abstract==


This abstract first appeared for US patent application 20240161488 titled 'INDEPENDENT POSITIONING OF AUXILIARY INFORMATION IN NEURAL NETWORK BASED PICTURE PROCESSING

==Simplified Explanation==

The patent application describes methods and apparatuses for processing picture data using a neural network with two or more layers, particularly in the field of neural network-based video compression technologies. 

* Neural network with multiple layers used for processing picture data
* Combining two kinds of data from different processing stages for better encoding/decoding performance
* Greater scalability and flexible design of neural network architecture

== Potential Applications ==
This technology can be applied in various fields such as video compression, image recognition, and data analysis.

== Problems Solved ==
This technology addresses the need for efficient processing and compression of picture data, improving encoding and decoding performance.

== Benefits ==
The use of a neural network with multiple layers allows for better scalability, flexibility, and performance in processing picture data.

== Potential Commercial Applications ==
This technology can be utilized in industries such as video streaming services, surveillance systems, medical imaging, and autonomous vehicles.

== Possible Prior Art ==
Prior art in the field of neural network-based video compression technologies may include research papers, patents, and existing products that utilize similar techniques.

=== Unanswered Questions ===

=== How does this technology compare to existing video compression methods? ===
This article does not provide a direct comparison with traditional video compression methods or other neural network-based approaches.

=== What are the limitations of using a neural network with multiple layers for picture data processing? ===
The article does not discuss any potential drawbacks or challenges associated with implementing this technology.


==Original Abstract Submitted==

this application provides methods and apparatuses for processing of picture data or picture feature data using a neural network with two or more layers. the present disclosure may be applied in the field of artificial intelligence (ai)-based video or picture compression technologies, and in particular, to the field of neural network-based video compression technologies. according to some embodiments, two kinds of data are combined during the processing including processing by the neural network. the two kinds of data are obtained from different stages of processing by the network. some of the advantages may include greater scalability and a more flexible design of the neural network architecture which may further lead to better encoding/decoding performance.



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[[Category:H04N19/513]]
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