V. Maha Vishnu, M. Rajalakshmi, R. Nedunchezhian, Intelligent traffic video surveillance and accident detection system with dynamic traffic signal control. Clust. Comput. 21, 135–147 (2018)

Article  Google Scholar 

V. Adewopo, N. Elsayed, Z. ElSayed, M. Ozer, A. Abdelgawad, M. Bayoumi, Review on action recognition for accident detection in smart city transportation systems. arXiv preprint arXiv:2208.09588 (2022).

Y. Yao, M. Xu, Y. Wang, D.J. Crandall, E.M. Atkins, Unsupervised traffic accident detection in first-person videos. In: 2019 IEEE/RSJ international conference on intelligent robots and systems (IROS), 273–280 (2019).

E. Batanina, I.E.I. Bekkouch, Y. Youssry, A. Khan, A.M. Khattak, M. Bortnikov, Domain adaptation for car accident detection in videos. In: 2019 ninth international conference on image processing theory, tools and applications (IPTA), 1–6 (2019).

X. Huang, P. He, A. Rangarajan, S. Ranka, Intelligent intersection: two-stream convolutional networks for real-time near-accident detection in traffic video. ACM Trans. Spat. Algorithms Syst. (TSAS) 6(2), 1–28 (2020)

Article  Google Scholar 

S.P. Shubham, M. Kumar, S. Jain, A survey on iot based automatic road accident detection. In: 2021 5th international conference on intelligent computing and control systems (ICICCS), 1–7 (2021)

M.C. Ang, K.W. NG, E. Sundararajan, Multi-core frameworks investigation on a real-time object tracking application. J. Theor. Appl. Inf. Technol. (2014).

M. Mogharrebi, M.C. Ang, A.S. Prabuwono, A. Aghamohammadi, K.W. Ng, Retrieval system for patent images. Procedia Technol. 11, 912–918 (2013)

Article  Google Scholar 

P. Ding, X. Liu, H. Li, Z. Huang, K. Zhang, L. Shao, O. Abedinia, Useful life prediction based on wavelet packet decomposition and two-dimensional convolutional neural network for lithium-ion batteries. Renew. Sustain. Energy Rev. 148, 111287 (2021)

Article  Google Scholar 

O. Abedinia, N. Amjady, Net demand prediction for power systems by a new neural network-based forecasting engine. Complexity 21(S2), 296–308 (2016)

Article  ADS  MathSciNet  Google Scholar 

V.S. Sindhu, Vehicle identification from traffic video surveillance using YOLOv4. In: 2021 5th international conference on intelligent computing and control systems (ICICCS), 1768–1775 (2021).

C. Wang, Y. Dai, W. Zhou, Y. Geng, A vision-based video crash detection framework for mixed traffic flow environment considering low-visibility condition. J. Adv. Transp. 2020 (2020).

M. Ang, E. Sundararajan, K. Ng, A. Aghamohammadi, T. Lim, Investigation of threading building blocks framework on real time visual object tracking algorithm. Appl. Mech. Mater. 666, 240–244 (2014)

Article  Google Scholar 

M.C. Ang, A. Aghamohammadi, K.W. NG, E. Sundararajan, M. Mogharrebi, T.L. Lim, Multi-core frameworks investigation on a real-time object tracking application. J. Theor. Appl. Inf. Technol. 70 (1), (2014)

H. Ghahremannezhad, H. Shi, C. Liu, Real-time accident detection in traffic surveillance using deep learning. In: 2022 IEEE international conference on imaging systems and techniques (IST), 1–6 (2022)

E.P. Ijjina, D. Chand, S. Gupta, K. Goutham, Computer vision-based accident detection in traffic surveillance. In: 2019 10th International conference on computing, communication and networking technologies (ICCCNT), 1–6 (2019)

Z. Zhou, X. Dong, Z. Li, K. Yu, C. Ding, Y. Yang, Spatio-temporal feature encoding for traffic accident detection in VANET environment. IEEE Trans. Intell. Transp. Syst. 23(10), 19772–19781 (2022)

Article  Google Scholar 

D. Tian, C. Zhang, X. Duan, X. Wang, An automatic car accident detection method based on cooperative vehicle infrastructure systems. IEEE Access 7, 127453–127463 (2019)

Article  Google Scholar 

C. Veena, M. Swathi, M. Harini, M. Rujula, A Vision-Based System Design and Implementation for Accident Detection and Analysis via Traffic Surveillance Video. Lampyrid J. Biolumin. Beetle Res. 13, 274–282 (2023)

Google Scholar 

A. Aghamohammadi, M.C. Ang, E.A. Sundararajan, N.K. Weng, M. Mogharrebi, S.Y. Banihashem, A parallel spatiotemporal saliency and discriminative online learning method for visual target tracking in aerial videos. PLoS ONE 13(2), e0192246 (2018)

Article  Google Scholar