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pro vyhledávání: '"Pavan Kumar Chaubey"'
Autor:
Pavan Kumar Chaubey, Tarun Kumar Arora, K. Bhavana Raj, G. R. Asha, Geetishree Mishra, Suresh Chand Guptav, Majid Altuwairiqi, Musah Alhassan
Publikováno v:
Computational Intelligence and Neuroscience. 2022:1-11
People are actively expressing their views and opinions via the use of visual pictures and text captions on social media platforms, rather than just publishing them in plain text as a consequence of technical improvements in this field. With the adve
Autor:
Mohamed Dawood Shamout, Pavan Kumar Chaubey, Priyanka Agarwal, Ibrahim A I Adwan, Anuj Kumar Sharma, Ajay Singh Yadav
Publikováno v:
2022 International Interdisciplinary Humanitarian Conference for Sustainability (IIHC).
Autor:
Tarun Kumar Arora, Pavan Kumar Chaubey, Manju Shree Raman, Bhupendra Kumar, Yagnam Nagesh, P. K. Anjani, Hamed M. S. Ahmed, Arshad Hashmi, S. Balamuralitharan, Baru Debtera
Publikováno v:
Computational Intelligence and Neuroscience.
Humans have traditionally found it simple to identify emotions from facial expressions, but it is far more difficult for a computer system to do the same. The social signal processing subfield of emotion recognition from facial expression is used in
Publikováno v:
Materials Today. Proceedings
In this paper, the determined economic impact of the Medicine industry of the Coronavirus pandemic for aggravating items with a ramp-type demand with inflation effects in two-warehouse storage devices and wastewater treatment cost using PSO is develo
Autor:
Tarun Kumar Arora, Pavan Kumar Chaubey
Publikováno v:
Materials Today: Proceedings.
Transportation problem (TP) possesses interval assessment methodology, in view of the multiple-choice environment. CTP parameters accompany the type of multi-choice interval-based value, and therefore this type of TP is named as MITP, popularly known
Autor:
Tarun Kumar Arora, Pavan Kumar Chaubey
Publikováno v:
Materials Today: Proceedings.
To enhance the reliability of the software, the prediction of software defects is being used to identify software bugs and prioritize testing efforts. Some authors have successfully adopted deep learning models, like the convolutional neural network
Autor:
S.S., Shukla, Pavan, Kumar Chaubey
Publikováno v:
Yokohama Mathematical Journal = 横濱市立大學紀要. D部門, 数学. 55(2):113-127