• Fatima Ansari
• Adil Khan
• Abhishekh Chaurasia
• Mohammed Faiz Khan
• Abdul Wahid Shaikh

Object detection is closely related to video analysis and image understanding, it has attracted researchers' attention over the recent years as technology advanced. Earlier object detection methods are built on handmade features and shallow trainable algorithms and architectures. Their performance easily saturates by giving them a complex image to computer vision. Human vision has got millions of years of evolution as a result human vision is fast reliable and accurate whereas the computer is century old, with exponential development of computer into a supercomputer, there exists rapid progress in deep learning, powerful tool, which are able to learn semantic segmentation, high level, deeper features to solve the traditional problem. Our model uses ssd mobile net algorithm to accurately detect objects in images. Our model generates a score in percent of the object present in the image.

object detection, image processing, realtime object , images

"Realtime Object Detection Using Ssd ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.8, Issue 10, page no.294-297, October-2021, Available :http://www.jetir.org/papers/JETIRFD06045.pdf

"Realtime Object Detection Using Ssd ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.8, Issue 10, page no. pp294-297, October-2021, Available at : http://www.jetir.org/papers/JETIRFD06045.pdf