Vaishnavi, K. and Reddy, G. Pranay and Reddy, T. Balaram and Iyengar, N. Ch. Srimannarayana and Shaik, Subhani (2023) Real-time Object Detection Using Deep Learning. Journal of Advances in Mathematics and Computer Science, 38 (8). pp. 24-32. ISSN 2456-9968
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Abstract
As technology improved, object detection, which is connected to video and image analysis, caught researchers' interest. Earlier object recognition techniques are based on hand-crafted features and imprecise architectures and trainable algorithms. One of the main issues with many object detection systems is that they rely on other computer vision methods to support their deep learning-based methodology, which leads to slow and subpar performance. In this article, we present an end-to-end solution to the object detection problem using a deep learning based method. The single shot detector (SSD) technique is the quickest method for object detection from an image using a single layer of a convolution network. Our research's primary goal is to enhance accuracy of SSD method.
Item Type: | Article |
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Subjects: | AP Academic Press > Computer Science |
Depositing User: | Unnamed user with email support@apacademicpress.com |
Date Deposited: | 16 Jun 2023 06:27 |
Last Modified: | 22 Oct 2024 04:11 |
URI: | http://info.openarchivespress.com/id/eprint/1577 |