A Comparison Study of Abnormal Human Activity Analysis

Author:

Ramalingam H. M.,Ajay ,Kotian Dishu,Sequeira Elroy

Publisher

Springer Nature Singapore

Reference12 articles.

1. Abhiram A, Kumar D, Sai Likhita K (2022) Suspicious human activity recognition and alarming system using CNN and LSTM algorithm [Online]. Available: https://ijariie.com/AdminUploadPdf/SUSPICIOUS_HUMAN_ACTIVITY_RECOGNITION__AND_ALARMING_SYSTEM_USING_CNN_AND__LSTM_ALGORITHM_ijariie16407.pdf. Accessed 31 Dec 2022

2. Papaleonidas A, Psathas AP, Iliadis L (2022) High accuracy human activity recognition using machine learning and wearable devices’ raw signals. J Inf Telecommun 6(3):237–253. https://doi.org/10.1080/24751839.2021.1987706

3. Andrew Joemon AP (2021) Abnormal event detection using CCTV Camera—Google Search. Int J Innov Sci Res Technol 1–5. ISSN No: 2456-2165 [Online]. Available: https://www.google.com/search?q=Abnormal+Event+Detection+Using+CCTV+Camera&rlz=1C1RXQR_enIN1007IN1007&oq=Abnormal+Event+Detection+Using+CCTV+Camera&aqs=chrome.69i57j35i39j69i59l2j69i60l3.343j0j9&sourceid=chrome&ie=UTF-8. Accessed 30 Dec 2022

4. Vrskova R, Hudec R, Kamencay P, Sykora P (2022) A new approach for abnormal human activities recognition based on ConvLSTM architecture. Sensors 22(8):2946. https://doi.org/10.3390/s22082946

5. Arshad MH, Bilal M, Gani A (2022) Human activity recognition: review, taxonomy and open challenges. Sensors 22(17):6463. https://doi.org/10.3390/s22176463

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