An Overview of the Type of Vehicle Detection Techniques

Subject Areas : Majlesi Journal of Telecommunication Devices

Mojtaba Nasehi ¹ (Student of Mobarakeh-Majlisi Branch of Azad University)
Mohsen Ashourian ² ()
Payman Moallem ³ ()

Received: 2020-08-18 Accepted : 2020-09-11 Published : 2020-09-01

Keywords:

References:

[1] B.D. Stewart, I. Reading, M.S. Thomson, T.D. Binnie, K.W. Dickinson, C.L. Wan, (1994). Adaptive lane finding in road traffic image analysis, Proceedings of Seventh International Conference on Road Traffic Monitoring and Control, IEE, London.

[2]W. Enkelmann, (1990). Obstacle detection by evaluation of optical flow field from image sequences, Proceedings of European Conference on Computer Vision, Antibes, France 427. 134–138.

[3]Y. Park, (2001), Shape-resolving local thresholding for object detection, Pattern Recognition Letters 22. 883–890.

[4] J.M. Blosseville, C. Krafft, F. Lenoir, V. Motyka, S. Beucher, (1994). New traffic measurements by image processing, IFAC Transportation systems, Tianjin, Proceedings.

[5]Y. Won, J. Nam, B.-H. Lee, (2001). Image pattern recognition in natural environment using morphological feature extraction, in: F.J. Ferri (Ed.), SSPR&SPR 2000, Springer, Berlin, pp.806–815.

[6]Zhigang, Zhou , Huan, Lei , Pengcheng, Ding , Guangbing, Zhou , Nan, Wang ,Wei-Kun, Zhou,( 2018). Vehicle target detection based on R-FCN, 2018 Chinese Control And Decision Conference (CCDC)

[7]Zhang, Zhaojin , Xu, Cunlu , Feng, Wei.(2016), Road vehicle detection and classification based on deep neural network. 2016 7th IEEE International Conference on Software Engineering and Service Science (ICSESS)

[8]Yu, Shaoyong , Wu, Yun , Li, Wei , Song, Zhijun , Zeng, Wenhua.(2017). A model for fine-grained vehicle classification based on deep learning, Neurocomputing

[9]Wang, Xinchen , Zhang, Weiwei , Wu, Xuncheng , Xiao, Lingyun , Qian, Yubin , Fang, Zhi.(2019). Real-time vehicle type classification with deep convolutional neural networks, Journal of Real-Time Image Processing

[10]Suhao, Li , Jinzhao, Lin , Guoquan, Li , Tong, Bai , Huiqian, Wang ,Yu, Pang.(2018). Vehicle type detection based on deep learning in traffic scene, Procedia computer science

[11]Sheng, Minglan , Liu, Chunfang , Zhang, Qi , Lou, Lu , Zheng, Yu.(2018) Vehicle Detection and Classification Using Convolutional Neural Networks, 2018 IEEE 7th Data Driven Control and Learning Systems Conference (DDCLS)

[12]Murali, Anju, Nair, Bhavana B, Rao, Sethuraman N(2018). Comparative Study of Different CNNs for Vehicle Classification, 2018 IEEE International Conference on Computational Intelligence and Computing Research (ICCIC)

[13]Li, Yinghua , Song, Bin . Kang, Xu . Du, Xiaojiang . Guizani, Mohsen.(2018). Vehicle-type detection based on compressed sensing and deep learning in vehicular networks,Sensors

[14]Kamran, Farrukh . Shahzad, Muhammad . Shafait, Faisal(2018). Automated military vehicle detection from low-altitude aerial images, 2018 Digital Image Computing: Techniques and Applications (DICTA)

[15]Hicham, Bensedik . Ahmed, Azough . Mohammed, Meknasssi(2018). Vehicle Type Classification Using Convolutional Neural Network, 2018 IEEE 5th International Congress on Information Science and Technology (CiSt)

[16]Ali, Mohamed Ashraf . El Munim, Hossam E Abd . Yousef, Ahmed Hassan . Hammad, Sherif(2018). A Deep Learning Approach for Vehicle Detection, 2018 13th International Conference on Computer Engineering and Systems (ICCES)

[17]X. Li, Z.-Q. Liu, K.-M. Leung, (2002). Detection of vehicles from traffic scenes using fuzzy integrals, Pattern Recognition 35. 967–980.

[18]H. Moon, R. Chellapa, A. Rosenfeld, (2003). Performance analysis of a simple vehicle detection algorithm, Image and Vision Computing 20. 1–13.

[19]G.D. Sullivan, K.D. Baker, A.D. Worrall, C.I. Attwood, P. M. Remagnino, (2004) Model-based vehicle detection and classification using orthographic approximations, Image and Vision Computing 15.