Biponjot Kaur
ABSTRACT
Object detection is one of the most critical and challenging tasks in computer vision. It is the process of finding objects belonging to some predefined categories and determining their location in an image or video. This paper reviews deep learning-based object detection models. The paper discusses some benchmark datasets. The performance evaluation of different detectors on different datasets based on mean Average Precision (mAP) is reviewed. Object detection is used in different fields in different forms. Applications of object detection like pedestrian detection, autonomous driving, face detection, etc., are presented. Finally, the future scope is discussed to work on new techniques for object detection.
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Index Terms
- Object Detection using Deep Learning: A Review
Index terms have been assigned to the content through auto-classification.
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