BibTeX:

@article{IJIRSTV5I7004,
     title={Object Detection using Single Shot Detector for a Self Driving Car},
     author={Vallae Haritha and Swetha M S},
     journal={International Journal for Innovative Research in Science & Technology},
     volume={5},
     number={7},
     pages={5--11},
     year={},
     url={http://www.ijirst.org/articles/IJIRSTV5I7004.pdf},
     publisher={IJIRST (International Journal for Innovative Research in Science & Technology)},
}

Object detection is a computer technology related to computer vision and image processing that deals with detecting, in digital images and videos, instances of semantic objects of a certain class, such as humans, buildings, cars, etc. Single Shot Multi Box Detector (SSD) is a deep learning method and one of the fastest algorithms which uses a single convolutional neural network to detect the object and also classify the stationary candidate objects in an image. SSD has the advantages of fast speed and high accuracy but is less accurate in detecting small objects compared to large objects. The proposed system is to use the SSD algorithm for a video simulation of a self-driving car to detect person and some suspected type of objects which include backpack, handbag, etc. quickly along with the curvature of the road and also to be able to use in a real time video.

Single Shot Multi Box Detector (SSD)