Zobrazeno 1 - 10
of 469
pro vyhledávání: '"Visual descriptors"'
Autor:
Itsaso Rodriguez-Moreno, Jose Maria Martinez-Otzeta, Izaro Goienetxea, Igor Rodriguez, Basilio Sierra
Publikováno v:
IEEE Access, Vol 9, Pp 139946-139957 (2021)
In this paper we report on the design of a pipeline involving Common Spatial Patterns (CSP), a signal processing approach commonly used in the field of electroencephalography (EEG), matrix representation of features and image classification to catego
Externí odkaz:
https://doaj.org/article/0de15198774f461aab1227d9a7f3ee72
Autor:
Rasha Shoitan, Mona M. Moussa, Sawsan Morkos Gharghory, Heba A. Elnemr, Young-Im Cho, Mohamed S. Abdallah
Publikováno v:
Sensors, Vol 23, Iss 3, p 1521 (2023)
During the last decade, surveillance cameras have spread quickly; their spread is predicted to increase rapidly in the following years. Therefore, browsing and analyzing these vast amounts of created surveillance videos effectively is vital in survei
Externí odkaz:
https://doaj.org/article/e069d76e834b478692f2afc2f7bba91b
Publikováno v:
Sensors, Vol 22, Iss 22, p 8635 (2022)
With a large number of Local Binary Patterns (LBP) variants being currently used today, the significant and importance of visual descriptors in computer vision applications are prominent. This paper presents a novel visual descriptor, i.e., SIM-LBP.
Externí odkaz:
https://doaj.org/article/9b1302bd1a4c476c9b93e2860791c1cf
Publikováno v:
Visual Computing for Industry, Biomedicine, and Art, Vol 2, Iss 1, Pp 1-13 (2019)
Abstract In the context of improved navigation for micro aerial vehicles, a new scene recognition visual descriptor, called spatial color gist wavelet descriptor (SCGWD), is proposed. SCGWD was developed by combining proposed Ohta color-GIST wavelet
Externí odkaz:
https://doaj.org/article/44f10ab1951b45b0a86e5c92dd7d11ec
Publikováno v:
Advances on Mechanics, Design Engineering and Manufacturing IV ISBN: 9783031159275
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e99b453bba0049d743397314978ac0fb
https://doi.org/10.1007/978-3-031-15928-2_69
https://doi.org/10.1007/978-3-031-15928-2_69
Autor:
Hong‐Bo Zhang, Qing Lei, Duan‐Sheng Chen, Bi‐Neng Zhong, Jialin Peng, Ji‐Xiang Du, Song‐Zhi Su
Publikováno v:
IET Computer Vision, Vol 10, Iss 6, Pp 528-536 (2016)
In this study, the authors investigate the possibility of boosting action recognition performance by exploiting the associated scene context. Towards this end, the authors model a scene as a mid‐level ‘middle layer’ in order to bridge action de
Externí odkaz:
https://doaj.org/article/1b12e7bad87e45bab8b071340ebc5d31
Autor:
Oluwole A. Adegbola, David O. Aborisade, Segun I. Popoola, Olatide A. Amole, Aderemi A. Atayero
Publikováno v:
Cogent Engineering, Vol 5, Iss 1 (2018)
Image retrieval via traditional Content-Based Image Retrieval (CBIR) often incurs the semantic gap problem—non-correlation of image retrieval results with human semantic interpretation of images. In this paper, Relevance Feedback (RF) mechanism was
Externí odkaz:
https://doaj.org/article/d1d9711a06a84fc48abda51b957c4b2b
Autor:
Amad Zafar, Manzar Masud, Muhammad Junaid Alvi, Sajid Saleem, Karam Dad Kallu, Muhammad Umair Ali, Haris Masood
Publikováno v:
International Journal of Energy Research. 46:774-785
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::db66703997f2dee58868ef3d12e53b94
https://doi.org/10.1002/er.7201
https://doi.org/10.1002/er.7201
Autor:
Andrea Loddo, Lorenzo Putzu
Publikováno v:
AI
Volume 2
Issue 3
Pages 25-412
AI, Vol 2, Iss 25, Pp 394-412 (2021)
Volume 2
Issue 3
Pages 25-412
AI, Vol 2, Iss 25, Pp 394-412 (2021)
Automating the analysis of digital microscopic images to identify the cell sub-types or the presence of illness has assumed a great importance since it aids the laborious manual process of review and diagnosis. In this paper, we have focused on the a
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4fe34803d5ecbcbe13d35a3566dee97c
https://doi.org/10.3390/ai2030025
https://doi.org/10.3390/ai2030025
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