Never forget, Its Freedom Deal. Use IRE15 promo code and Get 150 INR / 2 USD discount on processing charges. Promo offer valid from 5th August 2020 to 25th August 2020.

Designing a deep learning model to detect objects
  • Author(s): Chandan Gopal Vishwakarma ; Swapnil Sonawane ; Nikhil Mahadik ; Dr. J. W. Bakal
  • Paper ID: 1702435
  • Page: 113-120
  • Published Date: 31-07-2020
  • Published In: Iconic Research And Engineering Journals
  • Publisher: IRE Journals
  • e-ISSN: 2456-8880
  • Volume/Issue: Volume 4 Issue 1 July-2020
Abstract

Object detection is to identify objects in the image along with its localization and classification. This paper deals in the area of computer vision, mainly for the application of deep learning in the object detection task. On the one hand, there’s a straightforward summary of the dataset and deep learning algorithms commonly utilized in computer vision. There’s a literature survey of papers containing different current approaches like faster r-cnn, Yolo, etc. A literature survey is represented in tabular form with our inference.

Keywords

Object Detection, Dataset, Convolutional Neural Network, Computer Vision.

Citations

IRE Journals:
Chandan Gopal Vishwakarma , Swapnil Sonawane , Nikhil Mahadik , Dr. J. W. Bakal "Designing a deep learning model to detect objects" Iconic Research And Engineering Journals Volume 4 Issue 1 2020 Page 113-120

IEEE:
Chandan Gopal Vishwakarma , Swapnil Sonawane , Nikhil Mahadik , Dr. J. W. Bakal "Designing a deep learning model to detect objects" Iconic Research And Engineering Journals, 4(1)