Case Studies · Open access
Vehicle Detection Through Cnn
Abstract
In this work, a reliable and effective model for the identification of cars in traffic surveillance. Vehicle detection is achieved through the Operation of Convolutional Neural Networks (CNNs), combining high-level and low-level information using feature fusion techniques. The use of static pictures is highly applicable for various operations in traffic surveillance. This makes it possible to identify different-sized cars using different attributes. We get 99.4% training accuracy & 99.3% in testing accuracy.
Keywords
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Naim, M. M. H., Ayon, M. S. I., Hasan, M. K., Mia, M. S., & Khan, M. M. A. A. (2024). Vehicle Detection Through Cnn. International Journal of Advanced Computing and Intelligent System, 1(1), online first. https://doi.org/10.66917/ijacis.a000013
Naim, Md. Mehedi Hasan, et al. “Vehicle Detection Through Cnn.” International Journal of Advanced Computing and Intelligent System, vol. 1, no. 1, 2024, pp. online first. doi:10.66917/ijacis.a000013
Naim, Md. Mehedi Hasan, Md. Shafiul Islam Ayon, Md. Khaled Hasan, Md. Shohag Mia, and Mr. Md. Abbas Ali Khan. “Vehicle Detection Through Cnn.” International Journal of Advanced Computing and Intelligent System 1(1) (2024): online first. https://doi.org/10.66917/ijacis.a000013
Naim, M. M. H.; Ayon, M. S. I.; Hasan, M. K.; Mia, M. S.; Khan, M. M. A. A. (2024) ‘Vehicle Detection Through Cnn’, International Journal of Advanced Computing and Intelligent System, 1(1), pp. online first. doi:10.66917/ijacis.a000013
BibTeX
@article{msisijacis-a000013,
title = {Vehicle Detection Through Cnn},
author = {Md. Mehedi Hasan Naim and Md. Shafiul Islam Ayon and Md. Khaled Hasan and Md. Shohag Mia and Mr. Md. Abbas Ali Khan},
journal = {International Journal of Advanced Computing and Intelligent System},
year = {2024},
volume = {1},
number = {1},
doi = {10.66917/ijacis.a000013}
}Related articles
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