Scopus Indexed Publications

Paper Details


Title
Real-Time Object Detection using Machine Learning
Author
Md. Moshiur Rahman, Abdus Sattar, Dewan Mamun Raza, SADIA AKTER, Shajeeb Chakma,
Email
Abstract
Real-time-object-detection is object detection in authentic time with expeditious inference while maintaining a base level of precision. It is a cosmic, energetic yet uncertain and complicated space of PC vision. Because of its increased use in reconnaissance, the global positioning framework used in security and numerous other applications has moved scientists to never-ending device more severe and proficient calculations. In any case, difficulties arise in executing object identification and following in actual time, like following under robust climate, an excessive calculation to fit the accurate time execution, or multi-camera multiobjects following make this assignment exhaustingly burdensome. Item identification is a PC vision procedure that sanctions us to distinguish and find objects in a picture or video. Article identification sanctions us to immediately consign the sorts of things found while finding occasions of them inside the picture. However, numerous strategies and procedures have been grown, yet in this writing audit, we have examined some celebrated and straightforward techniques for object recognition and following. In the end, we have withal given their overall applications and results.

Keywords
Object Recognition , Image Processing , Machine Learning , Real Time Object
Journal or Conference Name
2021 12th International Conference on Computing Communication and Networking Technologies (ICCCNT)
Publication Year
2021
Indexing
scopus