American Psychological Association 6th edition

Bhaskar, T., Sathish, K., Salomi Victoria, D. R., Er. Tatiraju., Kanth, V. R., Patil, U., Mukkapati, N., Angadi, S., Karthikeyan, P., & Vidhya, R. G. (2025). Hybrid deep learning framework for enhanced target tracking in video surveillance using CNN and DRNN-GWO. International Journal of Basic & Applied Science, 14(1), 208-215. https://doi.org/10.14419/wddeck70

ISO-690 (author-date, English)

BHASKAR, Thupakula, SATHISH, K., SALOMI VICTORIA, D. Rosy, ER. TATIRAJU., KANTH, V. Rajani, PATIL, Uma, MUKKAPATI, Naveen, ANGADI, Sanjeevkumar, KARTHIKEYAN, P. und VIDHYA, R. G., 2025. Hybrid deep learning framework for enhanced target tracking in video surveillance using CNN and DRNN-GWO. International Journal of Basic & Applied Science. 1 Januar 2025. Vol. 14, no. 1, p. 208-215. DOI 10.14419/wddeck70.

Modern Language Association 9th edition

Bhaskar, T., K. Sathish, D. R. Salomi Victoria, Er. Tatiraju., V. R. Kanth, U. Patil, N. Mukkapati, S. Angadi, P. Karthikeyan, und R. G. Vidhya. „Hybrid Deep Learning Framework for Enhanced Target Tracking in Video Surveillance Using CNN and DRNN-GWO.“. International Journal of Basic & Applied Science, Bd. 14, Nr. 1, Januar 2025, S. 208-15, https://doi.org/10.14419/wddeck70.

Mohr Siebeck - Recht (Deutsch - Österreich)

Bhaskar, Thupakula/Sathish, K./Salomi Victoria, D. Rosy/Er. Tatiraju./Kanth, V. Rajani/Patil, Uma u. a.: Hybrid deep learning framework for enhanced target tracking in video surveillance using CNN and DRNN-GWO., International Journal of Basic & Applied Science 2025, 208-215.

Emerald - Harvard

Bhaskar, T., Sathish, K., Salomi Victoria, D.R., Er. Tatiraju., Kanth, V.R., Patil, U., Mukkapati, N., Angadi, S., Karthikeyan, P. und Vidhya, R.G. (2025), „Hybrid deep learning framework for enhanced target tracking in video surveillance using CNN and DRNN-GWO.“, International Journal of Basic & Applied Science, Vol. 14 No. 1, S. 208-215.

Achtung: Diese Zitate sind unter Umständen nicht zu 100% korrekt.