Concurrent Detection and Identification of Multiple Objects using YOLO Algorithm
The main purpose of this research paper is to study and report how the object detection and identification of multiple objects in an image or a video frameworks in real life. As part of this research, we have clearly presented about image classification, image localization, and image detection. The...
Uloženo v:
| Vydáno v: | Symposium of Image, Signal Processing, and Artificial Vision s. 1 - 6 |
|---|---|
| Hlavní autoři: | , , , |
| Médium: | Konferenční příspěvek |
| Jazyk: | angličtina |
| Vydáno: |
IEEE
15.09.2021
|
| Témata: | |
| ISSN: | 2329-6259 |
| On-line přístup: | Získat plný text |
| Tagy: |
Přidat tag
Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!
|
| Abstract | The main purpose of this research paper is to study and report how the object detection and identification of multiple objects in an image or a video frameworks in real life. As part of this research, we have clearly presented about image classification, image localization, and image detection. The entire work is carried out with the aid of YOLOv3 (You Only Look Once, Version 3) is an object detection algorithm which helps to detect real-time objects. YOLOv3 gives accurate results. It helps in declaring the localizers, classifiers, and detection. It uses a single neural network to the full image to detect the objects using bounding boxes thereby resulting in accurate outputs. The experiments and results show that YOLOv3 is extremely accurate. This rapidness in detecting objects is helpful in situations where humans can't detect with their naked eye cannot track multiple items simultaneously in an image or video frame. |
|---|---|
| AbstractList | The main purpose of this research paper is to study and report how the object detection and identification of multiple objects in an image or a video frameworks in real life. As part of this research, we have clearly presented about image classification, image localization, and image detection. The entire work is carried out with the aid of YOLOv3 (You Only Look Once, Version 3) is an object detection algorithm which helps to detect real-time objects. YOLOv3 gives accurate results. It helps in declaring the localizers, classifiers, and detection. It uses a single neural network to the full image to detect the objects using bounding boxes thereby resulting in accurate outputs. The experiments and results show that YOLOv3 is extremely accurate. This rapidness in detecting objects is helpful in situations where humans can't detect with their naked eye cannot track multiple items simultaneously in an image or video frame. |
| Author | Sriram, Ghali Megalingam, Rajesh Kannan YashwanthAvvari, Venkata Sai Babu, Dasari Hema Teja Anirudh |
| Author_xml | – sequence: 1 givenname: Rajesh Kannan surname: Megalingam fullname: Megalingam, Rajesh Kannan email: rajeshm@am.amrita.edu organization: Amrita Vishwa Vidyapeetham,Department of Electronics and Communication Engineering,Amritapuri,India – sequence: 2 givenname: Dasari Hema Teja Anirudh surname: Babu fullname: Babu, Dasari Hema Teja Anirudh email: dasari.anirudh278@ieee.org organization: Amrita Vishwa Vidyapeetham,Department of Electronics and Communication Engineering,Amritapuri,India – sequence: 3 givenname: Ghali surname: Sriram fullname: Sriram, Ghali email: sriramghali39@ieee.org organization: Amrita Vishwa Vidyapeetham,Department of Electronics and Communication Engineering,Amritapuri,India – sequence: 4 givenname: Venkata Sai surname: YashwanthAvvari fullname: YashwanthAvvari, Venkata Sai email: v.s.y.avvari@student.utwente.nl organization: University of Twente,Department of Electrical Engineering, Mathematics and Computer Science,The Netherlands |
| BookMark | eNotkMtOwzAURA0CiVL6BWz8Aym2b-L4LqvwilQUpBYkVlXsXBdXqVMl6YK_p4JuZqSjo1nMLbuKXSTGuBRzKQU-rNar8nORgTZmroSSc8xQCaku2AxzI7XO0lMYvGQTBQoTrTK8YbNh2AkhQBqDABP2XnTRHfue4sgfaSQ3hi7yOja8bE4s-ODqP9R5_nZsx3BoiVd2dxIHfhxC3PKvalnxRbvt-jB-7-_Yta_bgWbnnrKP56d18Zosq5eyWCyToASMCaEncGRBN9qAdnWaN423SmTeGJEhWp-n1qHzIvVKQ16TxbwBShWhsR6m7P5_NxDR5tCHfd3_bM4fwC97-VR7 |
| ContentType | Conference Proceeding |
| DBID | 6IE 6IL CBEJK RIE RIL |
| DOI | 10.1109/STSIVA53688.2021.9592012 |
| DatabaseName | IEEE Electronic Library (IEL) Conference Proceedings IEEE Proceedings Order Plan All Online (POP All Online) 1998-present by volume IEEE Xplore All Conference Proceedings IEEE Electronic Library (IEL) IEEE Proceedings Order Plans (POP All) 1998-Present |
| DatabaseTitleList | |
| Database_xml | – sequence: 1 dbid: RIE name: IEEE Electronic Library (IEL) url: https://ieeexplore.ieee.org/ sourceTypes: Publisher |
| DeliveryMethod | fulltext_linktorsrc |
| Discipline | Applied Sciences |
| EISBN | 9781665416689 1665416688 |
| EISSN | 2329-6259 |
| EndPage | 6 |
| ExternalDocumentID | 9592012 |
| Genre | orig-research |
| GroupedDBID | 6IE 6IF 6IK 6IL 6IN AAJGR AAWTH ABLEC ADZIZ ALMA_UNASSIGNED_HOLDINGS BEFXN BFFAM BGNUA BKEBE BPEOZ CBEJK CHZPO IEGSK IPLJI M43 OCL RIE RIL |
| ID | FETCH-LOGICAL-i203t-e9fe3ceb36d6836ca47ddfb205f880599bf74bc9cf04f2637aeb97d3e42e98bf3 |
| IEDL.DBID | RIE |
| ISICitedReferencesCount | 2 |
| ISICitedReferencesURI | http://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=Summon&SrcAuth=ProQuest&DestLinkType=CitingArticles&DestApp=WOS_CPL&KeyUT=001320078100024&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D |
| IngestDate | Wed Aug 27 02:25:12 EDT 2025 |
| IsPeerReviewed | false |
| IsScholarly | false |
| Language | English |
| LinkModel | DirectLink |
| MergedId | FETCHMERGED-LOGICAL-i203t-e9fe3ceb36d6836ca47ddfb205f880599bf74bc9cf04f2637aeb97d3e42e98bf3 |
| PageCount | 6 |
| ParticipantIDs | ieee_primary_9592012 |
| PublicationCentury | 2000 |
| PublicationDate | 2021-Sept.-15 |
| PublicationDateYYYYMMDD | 2021-09-15 |
| PublicationDate_xml | – month: 09 year: 2021 text: 2021-Sept.-15 day: 15 |
| PublicationDecade | 2020 |
| PublicationTitle | Symposium of Image, Signal Processing, and Artificial Vision |
| PublicationTitleAbbrev | STSIVA |
| PublicationYear | 2021 |
| Publisher | IEEE |
| Publisher_xml | – name: IEEE |
| SSID | ssj0003188933 |
| Score | 1.7844219 |
| Snippet | The main purpose of this research paper is to study and report how the object detection and identification of multiple objects in an image or a video... |
| SourceID | ieee |
| SourceType | Publisher |
| StartPage | 1 |
| SubjectTerms | anchor boxes bounding boxes CNN Deep Neural Networks image classification image localization Neural networks Object detection Planets Real-time systems Signal processing Signal processing algorithms Streaming media YOLOv3 |
| Title | Concurrent Detection and Identification of Multiple Objects using YOLO Algorithm |
| URI | https://ieeexplore.ieee.org/document/9592012 |
| WOSCitedRecordID | wos001320078100024&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D |
| hasFullText | 1 |
| inHoldings | 1 |
| isFullTextHit | |
| isPrint | |
| link | http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwlV1LSwMxEA61ePDkoxXf5ODRbXc3m2RzLGpR0LbQKvVU8pjUgu5Ku_X3m-yuFcGLtxASCDOZRybfzCB0GTm9yGNNg1BpGzh7bQLnJfAgiUIVyRSYZKZsNsEHg3Q6FaMGutrkwgBACT6Djh-Wf_km12sfKusKKpy9cgp3i3NW5Wpt4inubvrO8d9gnVB0x5Px_XOPEpZ6CFccdertv_qolGakv_u_A-yh9k8-Hh5tLM0-akB2gHZrBxLX4rlqoZFbr6uCS_gGihJllWGZGVzl49o6QIdzix9rJCEeKh-KWWGPgJ_jl-HDEPfe5vlyUby-t9FT_3ZyfRfULROCRRySIgBhgWj3QGaGpYRpmXBjrIpDap2gUiGU5YnSQtswsTEjXIIS3BBIYhCpsuQQNbM8gyOElQTKpWAQM50klEiwkGhlqWAqZUYdo5Yn0Oyjqooxq2lz8vf0KdrxPPBIi4ieoWaxXMM52tafxWK1vChZ-QWZFqEJ |
| linkProvider | IEEE |
| linkToHtml | http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwlV1LSwMxEA6lCnqq2opvc_DotvtIsptjUUuLfUGr1FPZJJNa0F1pt_5-k921InjxFkIIYSbzyOSbGYRuPKMXQ19SxxVSO8ZeK8d4CaFDPFd4cQQsZipvNhEOh9FsxscVdLvNhQGAHHwGTTvM__JVKjc2VNbilBt7ZRTuDiXEd4tsrW1ExdxO2zv-G67j8tZkOuk9t2nAIgvi8r1mucGvTiq5IenU_neEA9T4ycjD462tOUQVSI5QrXQhcSmg6zoam_WyKLmE7yHLcVYJjhOFi4xcXYbocKrxoMQS4pGwwZg1thj4BX4Z9Ue4_bZIV8vs9b2BnjoP07uuUzZNcJa-G2QOcA2BNE9kplgUMBmTUCktfJdqI6qUc6FDIiSX2iXaZ0EYg-ChCoD4wCOhg2NUTdIEThAWMdAw5gx8JgmhQQwaiBSaciYipsQpqlsCzT-KuhjzkjZnf09fo73udNCf93vDx3O0b_lhcRcevUDVbLWBS7QrP7PlenWVs_ULJb6kUA |
| openUrl | ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Abook&rft.genre=proceeding&rft.title=Symposium+of+Image%2C+Signal+Processing%2C+and+Artificial+Vision&rft.atitle=Concurrent+Detection+and+Identification+of+Multiple+Objects+using+YOLO+Algorithm&rft.au=Megalingam%2C+Rajesh+Kannan&rft.au=Babu%2C+Dasari+Hema+Teja+Anirudh&rft.au=Sriram%2C+Ghali&rft.au=YashwanthAvvari%2C+Venkata+Sai&rft.date=2021-09-15&rft.pub=IEEE&rft.eissn=2329-6259&rft.spage=1&rft.epage=6&rft_id=info:doi/10.1109%2FSTSIVA53688.2021.9592012&rft.externalDocID=9592012 |