KFU. Card publication. Surveillance Video-Based Object Detection by Feature Extraction and Classification Using Deep Learning Architecture

KAZAN
FEDERAL UNIVERSITY

- RUS
- 中文
- ES

SURVEILLANCE VIDEO-BASED OBJECT DETECTION BY FEATURE EXTRACTION AND CLASSIFICATION USING DEEP LEARNING ARCHITECTURE

Form of presentation

Articles in international journals and collections

Year of publication

2023

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Authors, employees of KFU

Akhmetshin Elvir Munirovich, author

Bibliographic description in the original language

Akhmetshin E, Sultanova S, Anupama C.S.S, Surveillance Video-Based Object Detection by Feature Extraction and Classification Using Deep Learning Architecture//Smart Innovation, Systems and Technologies. - 2023. - Vol.371, Is.. - P.369-378.

Annotation

As of late, deep learning has accomplished top exhibitions in object recognition undertakings. Be that as it may, continuously, frameworks having memory or processing restrictions extremely wide and profound organizations with various boundaries comprise a significant impediment. Profound gaining-based object location arrangements arose out of PC vision has spellbound undivided focus as of late. This examination proposes novel method in observation video-based object location by highlight extraction with characterization utilizing profound learning. Here the info information has been gathered as observation video and handled for commotion expulsion, smoothening, standardization. Then, at that point, the handled video has been separated and ordered utilizing concealed convolution fluffy perception brain organizations.

Keywords

Deep learning

The name of the journal

Smart Innovation, Systems and Technologies

URL

https://www.scopus.com/inward/record.uri?eid=2-s2.0-85178643635&doi=10.1007%2f978-981-99-6706-3_32&partnerID=40&md5=81dccc13633d73149df0ce487c7407a7

Please use this ID to quote from or refer to the card

https://repository.kpfu.ru/eng/?p_id=292707&p_lang=2

Full metadata record

Field DC	Value	Language
dc.contributor.author	Akhmetshin Elvir Munirovich	ru_RU
dc.date.accessioned	2023-01-01T00:00:00Z	ru_RU
dc.date.available	2023-01-01T00:00:00Z	ru_RU
dc.date.issued	2023	ru_RU
dc.identifier.citation	Akhmetshin E, Sultanova S, Anupama C.S.S, Surveillance Video-Based Object Detection by Feature Extraction and Classification Using Deep Learning Architecture//Smart Innovation, Systems and Technologies. - 2023. - Vol.371, Is.. - P.369-378.	ru_RU
dc.identifier.uri	https://repository.kpfu.ru/eng/?p_id=292707&p_lang=2	ru_RU
dc.description.abstract	Smart Innovation, Systems and Technologies	ru_RU
dc.description.abstract	As of late, deep learning has accomplished top exhibitions in object recognition undertakings. Be that as it may, continuously, frameworks having memory or processing restrictions extremely wide and profound organizations with various boundaries comprise a significant impediment. Profound gaining-based object location arrangements arose out of PC vision has spellbound undivided focus as of late. This examination proposes novel method in observation video-based object location by highlight extraction with characterization utilizing profound learning. Here the info information has been gathered as observation video and handled for commotion expulsion, smoothening, standardization. Then, at that point, the handled video has been separated and ordered utilizing concealed convolution fluffy perception brain organizations.	ru_RU
dc.language.iso	ru	ru_RU
dc.subject		ru_RU
dc.title	Surveillance Video-Based Object Detection by Feature Extraction and Classification Using Deep Learning Architecture	ru_RU
dc.type	Articles in international journals and collections	ru_RU