Strategies and Tools for Effective Suspicious Event Detection from Video: A Survey Perspective (COVID-19)
Author:
Mahmood Ali MohammedORCID, Qaseem Mohammed S., Rahman Ateeq ur
Publisher
Springer Singapore
Reference29 articles.
1. Ali, M.M., Qaseem, M.S., Rasheed, M.A., Khan, M.K.A.: ESMD: Enhanced suspicious message detection framework in instant messaging applications. In: Fourth International Conference on Inventive Systems and Control (ICISC), IEEE, pp. 777–784 (2020) 2. Sheu, R.-K., Pardeshi, M., Chen, L.-C., YuanKe, S.-M., Kim, H.D.-S.: STAM-CCF: Suspicious tracking across multiple camera based on correlation filters. sensors (Basel) J. 19(13) (2019) 3. Ali, M.M., Rahman, M.A.U., Hajera, S.: A comparative study of various image dehazing techniques. In: Proceedings of International Conference on Energy, Communication, Data Analytics and Soft Computing (ICECDS), IEEE, pp. 3622–3628 (2017) 4. Mahmood Ali, M., Moizuddin Mohammed, K., Rajamani, L.: Framework for surveillance of instant messages in instant messengers and social networking sites using data mining and ontology, IEEE-Students’ Technology Symposium (2014) 5. Amrutha, C. ., Jyotsna, C., Amudha, J.: Deep learning approach for suspicious activity detection from surveillance video. In: International Conference on Innovative Mechanisms for Industry Applications (ICIMIA) (2020)
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