Traffic Congestion Detection from Camera Images Using Deep Learning Approach
Author:
Publisher
Springer Nature Singapore
Link
https://link.springer.com/content/pdf/10.1007/978-981-97-5504-2_36
Reference15 articles.
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2. Alom, M.Z., et al.: A state-of-the-art survey on deep learning theory and architectures. Electronics 8(3), 292 (2019)
3. Balcilar, M., Sönmez, A.C.: Extracting vehicle density from background estimation using Kalman filter. In: 2008 23rd International Symposium on Computer and Information Sciences, ISCIS 2008 (2008)
4. Bui, K.H.N., Jung, J.J.: ACO-based dynamic decision making for connected vehicles in IoT system. IEEE Trans. Ind. Inform. 15, 5648–5655 (2019)
5. Chen, M., Yu, X., Liu, Y.: PCNN: deep convolutional networks for short-term traffic congestion prediction. IEEE Trans. Intell. Transp. Syst. 19(11), 3550–3559 (2018)
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