Digital Image Processing

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Implementation of Faster Region Based Convolutional Neural Network for Object Detection and Counting


Affiliations
1 Department of Telecommunication Engineering, Dayananda Sagar College of Engineering, Bangalore, Karnataka, India
2 Department of Telecommunication Engineering, Dayananda Sagar College of Engineering, Bangalore, Karnataka, India
     

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Traffic congestion is a growing concern in many developing nations, although congestion has a variety of negative consequences, including discouraging potential economic growth, rising automobile emissions, increasing fuel cost and many more. To overcome this issue, the deep learning Faster Region based Convolutional Neural Network(R-CNN) can be utilized to recognizes the objects. Faster R-CNN detects and counts the vehicles and pedestrians in a target street.

Keywords

Convolution Neural Network, Faster R-CNN, Feature Map, Object Detection, Region Proposal Network (RPN).
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  • Eduardo Jr Piedad, Tuan-Tang Le , Kimberly Aying Fhenyl Kristel Pama and Ianny Tabale. Cebu City, Philippines. (2019). Vehicle Count System based on Time Interval Image Capture Method and Deep Learning Mask R-CNN. IEEE, 5. doi:978-1-7281-1895-6/19

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  • Implementation of Faster Region Based Convolutional Neural Network for Object Detection and Counting

Abstract Views: 138  |  PDF Views: 0

Authors

C. P. Keerthana
Department of Telecommunication Engineering, Dayananda Sagar College of Engineering, Bangalore, Karnataka, India
N. K. Keerthana
Department of Telecommunication Engineering, Dayananda Sagar College of Engineering, Bangalore, Karnataka, India
U. Keerthana
Department of Telecommunication Engineering, Dayananda Sagar College of Engineering, Bangalore, Karnataka, India
S. Yeshaswini
Department of Telecommunication Engineering, Dayananda Sagar College of Engineering, Bangalore, Karnataka, India
Anitha Suresh
Department of Telecommunication Engineering, Dayananda Sagar College of Engineering, Bangalore, Karnataka, India

Abstract


Traffic congestion is a growing concern in many developing nations, although congestion has a variety of negative consequences, including discouraging potential economic growth, rising automobile emissions, increasing fuel cost and many more. To overcome this issue, the deep learning Faster Region based Convolutional Neural Network(R-CNN) can be utilized to recognizes the objects. Faster R-CNN detects and counts the vehicles and pedestrians in a target street.

Keywords


Convolution Neural Network, Faster R-CNN, Feature Map, Object Detection, Region Proposal Network (RPN).

References