Role Of Machine Learning In Object Detection: A Review
|International Journal of Engineering Trends and Technology (IJETT)||
|© 2019 by IJETT Journal|
|Year of Publication : 2019|
|Authors : Abirami ,Kavinila K, Kavitha T
|DOI : 10.14445/22315381/IJETT-V67I5P233|
MLA Style: Abirami ,Kavinila K, Kavitha T"Role Of Machine Learning In Object Detection: A Review" International Journal of Engineering Trends and Technology 67.5 (2019):192-194.
APA Style:Abirami ,Kavinila K, Kavitha T(2019).Role Of Machine Learning In Object Detection: A Review International Journal of Engineering Trends and Technology,67(5),192-194
In the eminent era of breakthrough in technology, the world is presented with a boon and bane. The need for machines is inevitable as they have become a part of human source. Our human vision is capable of capturing the object or image and identifies the captured input. When a massive data set is given as input along with required GPUs and algorithm which consumes less computation time and provides output with high accuracy, the computers are skilled to detect and classify the captured input. Artificial Neural Network is one such technique to train the machine to have a skill set. Particularly, Machine Learning plays a major role in detecting and classifying the objects using various algorithms. ML is widely used in tracking, face recognition, video surveillance, etc. The detected object’s characteristics are classified as classes using algorithms. The necessity for object detection emerged when the object needs to be identified from the images and video sources. Over the years, many algorithms were replaced by the latest and efficient algorithms which detected the objects with high accuracy rate. The performances of certain algorithms used in object detection will be discussed with their respective pros and cons. The solved and unsolved issues using Machine Learning algorithms are discussed in this paper.
 Christian Szegedy Alexander Toshev Dumitru Erhan, “Deep Neural Networks for Object Detection” , 2013
Artificial Neural Networks, Machine Learning, Object Detection