A Review of Object Detection Models based on Convolutional Neural
Network
F. Sultana, A. Sufian, and P. Dutta. (2019)cite arxiv:1905.01614Comment: 7 pages, 10 figures, 1 table, Submitted to 2nd International Conference on Communication, Devices and Computing(ICCDC 2019).
Abstract
Convolutional Neural Network (CNN) has become the state-of-the-art for object
detection task. In this paper, we have explained different object detection
models based on CNN. We have categorized those detection models according to
two different approaches: two-stage approach and one-stage approach. Through
this paper, we have shown advancements in object detection model from R-CNN to
latest RefineDet. We have discussed the model description and training details
of each model. We have also drawn a comparison among those models.
Description
[1905.01614] A Review of Object Detection Models based on Convolutional Neural Network
cite arxiv:1905.01614Comment: 7 pages, 10 figures, 1 table, Submitted to 2nd International Conference on Communication, Devices and Computing(ICCDC 2019)
%0 Generic
%1 sultana2019review
%A Sultana, F.
%A Sufian, A.
%A Dutta, P.
%D 2019
%K 2019 arxiv cnn detection review
%T A Review of Object Detection Models based on Convolutional Neural
Network
%U http://arxiv.org/abs/1905.01614
%X Convolutional Neural Network (CNN) has become the state-of-the-art for object
detection task. In this paper, we have explained different object detection
models based on CNN. We have categorized those detection models according to
two different approaches: two-stage approach and one-stage approach. Through
this paper, we have shown advancements in object detection model from R-CNN to
latest RefineDet. We have discussed the model description and training details
of each model. We have also drawn a comparison among those models.
@misc{sultana2019review,
abstract = {Convolutional Neural Network (CNN) has become the state-of-the-art for object
detection task. In this paper, we have explained different object detection
models based on CNN. We have categorized those detection models according to
two different approaches: two-stage approach and one-stage approach. Through
this paper, we have shown advancements in object detection model from R-CNN to
latest RefineDet. We have discussed the model description and training details
of each model. We have also drawn a comparison among those models.},
added-at = {2019-09-17T21:14:31.000+0200},
author = {Sultana, F. and Sufian, A. and Dutta, P.},
biburl = {https://www.bibsonomy.org/bibtex/222984fac68d74e705f3ba19f00b46735/analyst},
description = {[1905.01614] A Review of Object Detection Models based on Convolutional Neural Network},
interhash = {74799c8dc4c90a3991f7e89cb69fa4f3},
intrahash = {22984fac68d74e705f3ba19f00b46735},
keywords = {2019 arxiv cnn detection review},
note = {cite arxiv:1905.01614Comment: 7 pages, 10 figures, 1 table, Submitted to 2nd International Conference on Communication, Devices and Computing(ICCDC 2019)},
timestamp = {2019-09-17T21:14:31.000+0200},
title = {A Review of Object Detection Models based on Convolutional Neural
Network},
url = {http://arxiv.org/abs/1905.01614},
year = 2019
}