articleMar 1, 2020Closed access

YOLO v3-Tiny: Object Detection and Recognition using one stage improved model

Delhi Technological University

Indexed incrossref

Abstract

Object detection has seen many changes in algorithms to improve performance both on speed and accuracy. By the continuous effort of so many researchers, deep learning algorithms are growing rapidly with an improved object detection performance. Various popular applications like pedestrian detection, medical imaging, robotics, self-driving cars, face detection, etc. reduces the efforts of humans in many areas. Due to the vast field and various state-of-the-art algorithms, it is a tedious task to cover all at once. This paper presents the fundamental overview of object detection methods by including two classes of object detectors. In two stage detector covered algorithms are RCNN, Fast RCNN, and Faster RCNN,…

Citation impact

532
total citations
FWCI
28.34
Percentile
100%
References
32
Citations per year

Authors

3

Topics & keywords

Keywords
  • Object detection
  • Artificial intelligence
  • Detector
  • Computer science
  • Viola–Jones object detection framework
  • Object (grammar)
  • Pedestrian detection
  • Field (mathematics)
UN Sustainable Development Goals
  • Sustainable cities and communities
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