Toreyin, B., & Cetin, A. (2007). Online detection of fire in video. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 1-5. Minneapolis.

Tozhiyev, M., Primqulov, O., & Khasanov, D. (n.d.). Image segmentation in OpenCV and Python. doi:10.5958/2249-7137.2020.01735.8

Tumblin, J., & Rushmeier, H. (1993). Tone reproduction for realistic images. IEEE Comput. Graph. Appl.(13), pp. 42-48.

Xolboyevich, A. (2022). Pythonda chiziqli regressiya [Linear Regression in Python]. International Journal of Contemporary Scientific and Technical Research, pp. 233-238.

Zhang, J., Zhuang, J., & Du, H. (2006). A new flame detection method using probability model. Proceedings of the International Conference on Computational Intelligence and Security, pp. 1614–1617.

Celik, T., Demirel, H., Ozkaramanli, H., & Uyguroglu, M. (2006). Fire detection using statistical colour model in video sequences. Proceedings of the IEEE International Conference on Acoustics, Speech and Signal, pp. 213-216.

Celik, T., Ozkaramanli, H., & Demirel, H. (2007). Fire and smoke detection without sensors: image processing based approach. Proceedings of the European Signal Processing Conference.

Chen, T., Wu, P., & Chiou, Y. (2004). An early fire-detection method based on image processing. Proceedings of the IEEE International Conf. on Image Processing (ICIP), pp. 1707-1710.

Drago, F., Myszkowski, K., Annen, T., & Chiba, N. (2003). Adaptive logarithmic mapping for displaying high contrast scenes. Comput. Graph. Forum(22), pp. 419-426.

Duan, J., Bressan, M., Dance, C., & Qui, G. (2010). Tone-mapping high dynamic range images by novel histogram adjustment. Pattern Recognit(43), pp. 1847–1862.

Durand, F., & Dorsey, J. (2000). Interactive Tone Mapping, in: Rendering Techniques. Proceedings of the Eurographics Workshop, (pp. 219-230). Brno, Czech Republic.

Durand, F., & Dorsey, J. (2002). Fast Bilateral Filtering for the Display of High-Dynamic-Range Images. ACM Trans. Gr.(21), pp. 257-299.

Ferradans, S., Bertalmio, M., Provenzi, E., & Caselles, V. (2011). An analysis of visual adaptation and contrast perception for tone mapping. Pattern Anal. Mach. Intell.(33), pp. 2002-2012.

Ferwerda, J., Pattanaik, S., Shirley, P., & Green-Berg, D. (1996). A model of visual adaptation for realistic image synthesis. Proceedings of the 23rd Annual Conference on Computer Graphics and Interactive Techniques, (p. 98). New York.

Khasanov, D., Tojiyev, M., & Primqulov, O. (n.d.). Gradient Descent In Machine. Proceedings oif the International Conference on Information Science and Communications Technologies (ICISCT). Retrieved from https://ieeexplore.ieee.org/document/9670169

Larson, G., Rushmeier, H., & Piatko, C. (1997). A visibility matching tone reproduction operator for high dynamic range scenes. IEEE Trans. Vis. Comput. Graph.(3), pp. 291-306.

Philips, W., Shah, M., & Lobo, N. (2007). Flame recognition in video. Istanbul.

Reinhard, E., Stark, M., & Shirley, P. (2002). Photographic tone reproduction for digital images. ACM Trans. Graph.(21), pp. 267-276.

Ruzikulovich, T. (2022). Neyron tarmoq algoritmlari yordamida murakkab fondagi belgilarni aniqlash algoritmlari [Algorithms for detecting characters in complex backgrounds using neural network algorithms]. International Journal of Contemporary Scientific and Technical Research, pp. 238-241.

Tojiyev, M., Shirinboyev, R., & Sulaymonova, M. (2022). OpenCV kutubxonasida tasvirlarga rang modellari bilan ishlov berish [Processing images with color models in the OpenCV library]. Current Problems and Development Trends of modern Innovation Research: Solutions and Perspectives, 1(1), pp. 212-215.

Tojiyev, M., Ulug‘murodov, S., & Shirinboyev, R. (2022). Tasvirlar sifatini yaxshilashning chiziqli kontrast usuli [A linear contrast method for improving the quality of images]. Current Problems and Development Trends of Modern Innovation Research: Solutions and Perspectives, 1(1), pp. 215-217.