Please use this identifier to cite or link to this item:
http://ir.juit.ac.in:8080/jspui/jspui/handle/123456789/10181
Title: | Saliency Guided Faster R-CNN for object detection and Recognition |
Authors: | Kumar, Gulshan Sharma, Vipul [Guided by] |
Keywords: | Object detection Neural network Machine learning Deep learning |
Issue Date: | 2023 |
Publisher: | Jaypee University of Information Technology, Solan, H.P. |
Abstract: | The major purpose of our project to dectect object using faster R-CNN to develop a technique for programmed object finding and counting on throughways. Our method does not rely on foundation; rather, it employs a channel through which we identify and count the cars, record a video or a photograph, and then make a decision to give the total number of object. The purpose of this approach is to create a superior object detector structure inside the project for smoother detection of object flow and to increase a overall efficiency. |
Description: | Enrollment No. 191341 |
URI: | http://ir.juit.ac.in:8080/jspui/jspui/handle/123456789/10181 |
Appears in Collections: | B.Tech. Project Reports |
Files in This Item:
File | Description | Size | Format | |
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Saliency Guided Faster R-CNN for object detection and Recognition.pdf | 1.53 MB | Adobe PDF | View/Open |
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