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  Published Paper Details:

  Paper Title

Real-time Object Detection using the YOLO Algorithm with the OpenCV Framework

  Authors

  Shaik Ishrath Anjum,  Syed Roohi,  Vibudi Divya,  Venicherla Bhargavi,  B. Avinash

  Keywords

Computer Vision, Object Detection, YOLO algorithm, Deep Learning, Open-CV, COCO dataset.

  Abstract


In the realm of computer vision, object detection poses a significant challenge, especially in accurately localizing and categorizing objects within images. This paper introduces a novel method that utilizes a pre-trained deep learning model to detect objects in real time by processing webcam-captured images and video streams. Leveraging the renowned speed and accuracy of the YOLO algorithms, the system efficiently counts and monitors specific objects in each video frame, making it especially apt for visualization-focused applications. By integrating the YOLO model with the COCO dataset, the approach outperforms existing techniques in terms of precision and real-time responsiveness.

  IJCRT's Publication Details

  Unique Identification Number - IJCRT2310510

  Paper ID - 245461

  Page Number(s) - e558-e564

  Pubished in - Volume 11 | Issue 10 | October 2023

  DOI (Digital Object Identifier) -   

  Publisher Name - IJCRT | www.ijcrt.org | ISSN : 2320-2882

  E-ISSN Number - 2320-2882

  Cite this article

  Shaik Ishrath Anjum,  Syed Roohi,  Vibudi Divya,  Venicherla Bhargavi,  B. Avinash,   "Real-time Object Detection using the YOLO Algorithm with the OpenCV Framework", International Journal of Creative Research Thoughts (IJCRT), ISSN:2320-2882, Volume.11, Issue 10, pp.e558-e564, October 2023, Available at :http://www.ijcrt.org/papers/IJCRT2310510.pdf

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ISSN: 2320-2882
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ISSN and 7.97 Impact Factor Details


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ISSN: 2320-2882
Impact Factor: 7.97 and ISSN APPROVED
Journal Starting Year (ESTD) : 2013
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