Development of object identification model with deep reinforcement learning algorithm
P. Ramesh Naiduramesh.naidu@nmit.ac.inDepartment of Computer Science and EngineeringNitte Meenakshi Institute of TechnologyBangalore, Karnataka, IndiaView full profile → , Avinash Sharmaasharma@mmumullana.orgDepartment of Computer Science & EngineeringM. M. Engineering CollegeMaharishi Markandeshwar (Deemed To Be) UniversityMullana, Ambala, IndiaView full profile → , Supriya P. Diwansupriya.diwan8@gmail.comDepartment of Electronics and Telecommunication EngineeringGovernment College of EngineeringKarad, Satara, Maharashtra, IndiaView full profile → , *V. Dankan GowdaCorresponding authordankan.v@bmsit.inDepartment of Electronics and Communication EngineeringBMS Institute of Technology and ManagementBangalore, Karnataka, IndiaView full profile → , Parth M. Pandyapandyaparth05@gmail.comDepartment of MathematicsIndus UniversityAhmedabad, Gujarat, IndiaView full profile → , Anand Kumar GuptaGanand40@yahoo.co.inDepartment of Information TechnologyBlueCrest UniversityMonrovia, LiberiaView full profile →
* Corresponding author · click or hover a name for details
- Published Online:
- 11 Aug 2023
- Article type:
- Research Article
- Language:
- EN
- Article no.:
- JIOS-1346
- Pages:
- 355–367
Abstract
Keywords
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References
[1] C. C. Alves, S. Rabello, and K. M. de Carvalho.,“Assistive technology applied to education of students with visual impairment,” Salud Pública, vol. 26, no. 2, pp. 148-152 (2019).
[2] D. McAllester, R. B. Girshick., “Object detection with discriminatively trained part based models” IEEE Trans on Pattern Analysis and Machine Intelligence, 1627-1645 (2018).
[3] Ravi Prakash, “Small object detection using retinanet with hybrid anchor box hyper tuning using interface of Bayesian mathematics,” Journal of Information and Optimization Sciences, 43:8, 2099-2110 (2022).
[4] G. Bai, Q. Dong.,”Cube CNN SVM A novel hyper spectral image classification method” Proceeding IEEE 28 ICTAI, November 2019, page 1027-1034 (2019).
[5] P. Pavankumar, N. K. Darwante, “Performance Monitoring and Dynamic Scaling Algorithm for Queue Based Internet of Things,” 2022 International Conference on Innovative Computing, Intelligent Communication and Smart Electrical Systems (ICSES), pp. 1-7 (2022).
[6] Jyothi Varanasi & M. M. Tripathi, “K-means clustering based photo voltaic power forecasting using artificial neural network, particle swarm optimization and support vector regression,” Journal of Information and Optimization Sciences, 40:2, 309-328 (2019).
[7] Huiqi Zhu, “Strategies for adopting unified object identifiers in logistics resource integration environments,” Journal of Discrete Mathematical Sciences and Cryptography, 21:4, 991-1003 (2018).
[8] A. Singla, N. Sharma, “IoT Group Key Management using Incremental Gaussian Mixture Model,” 2022 3rd International Conference on Electronics and Sustainable Communication Systems (ICESC), pp. 469-474 (2022).
[9] Yang Jiao & Song Zhao, “Object tracking from airborne video using particle filters algorithm on dynamic feature fusion,” Journal of Discrete Mathematical Sciences and Cryptography, 19:3, 787-799 (2016).
[10] Jan K Chorowski, and Yoshua Bengio.,“Attention-based models for speech recognition” In Advances in neural information processing systems, pages 577-585 (2020).
[11] A. S. Naik, R. S. Meena, J. M. Kudari and S. Purushotham, “Design and Implementation of a System for Vehicle Accident Reporting and Tracking,” 2022 7th International Conference on Communication and Electronics Systems (ICCES), pp. 349-353 (2022).
[12] Juan C Caicedo and Svetlana Lazebnik., “Active object localization with deep reinforcement learning” In Proceedings of the IEEE Inter. Conference on ComputerVision, 2018, pages 2488-2496 (2018).
[13] Liu, W., Anguelov, D., Erhan, D., Szegedy, C., Reed, S., Fu, C.-Y., and Berg, A. C. Ssd., Single shot multibox detector. In European Conference on Computer Vision (2016), Springer, pp. 21-37 (2016).
[14] M. Oquab I. Laptev, and J. Sivic., “Learning and transferring mid-level image representations using convolutional neural networks” in Proc. IEEE Conf. Comput. Vis.Pattern Recognit., Jun. 2014, pp. 1717-1724 (2014).
[15] N. Srivastava, A. Krizhevsky and R. Salakhutdinov.,“Dropout: A simple way to prevent neural networks from over fitting,” J. Mach. Learn. Res., vol. 15, no. 1, pp. 1929-1958 (2020).
[16] M. Nagabushanam, H. G. Govardhana Reddy & K. Raghavendra, “Vector space modelling-based intelligent binary image encryption for secure communication,” Journal of Discrete Mathematical Sciences and Cryptography, 25:4, pp.1157-1171 (2022).
[17] Ross Girshick., “Convolutional neural net” In Proceedings of the IEEE international conference on computer vision, pages 1440-1448 (2020).
[18] S. Gupta and J. Malik.,“Perceptual organization and recognition of indoor scenes from RGB-D images,” in Proc. IEEE Conf. Comput. Vis. Pattern Recognit., Jun. 2019, pp. 564-571 (2019).
[19] M. Sahana, R. S. Varun, and T. Rajesh, “Implementation of swarm intelligence in obstacle avoidance,” in 2nd IEEE International Conference on Recent Trends in Electronics, Information and Communication Technology, Proceedings, vol. 2018-January, pp. 525–528 (2017).
[20] Sangdoo Yun, Yoo, Jongwon Choi.,“Action-Decision Networks for Visual Tracking with Deep Reinforcement Learning” IEEE Conf. on Computer Vision and Pattern Recognition (CVPR), pp. 101-120 (2017).
[21] Steinkraus, D., Buck, I., and Simard, P. “GPU for machine learning algorithms.” In Document Analysis and Recognition, 2005. Pro-ceedings. Eighth International Conference on (2015), IEEE, pp. 1115-1120 (2015).
[22] Triggs, B. and Dalal, N.,“Histograms of oriented gradients for human detection” In Computer Vision and Pattern Recognition, CVPR 2018. IEEE Computer Society Conference on 2018, vol. 1, IEEE, page 886-893 (2018).




