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3 January 2024

Correction: Nayak et al. Brain Tumour Classification Using Noble Deep Learning Approach with Parametric Optimization through Metaheuristics Approaches. Computers 2022, 11, 10

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1
School of Engineering and Technology (CSE), GIET University, Gunupur 765022, India
2
School of Computer Engineering, Kalinga Institute of Technology, Deemed to be University, Bhubaneswar 751024, India
3
Department of Mechanical Engineering, Government College of Engineering, Bhawanipatna 766002, India
4
Department of Computer Science, South Ural State University, 454080 Chelyabinsk, Russia

Figure Update

The original Figure 4 was not clear, the author would like to update it with a higher quality version.
Figure 4. Result of the sunflower optimization approach.
Figure 4. Result of the sunflower optimization approach.
Computers 13 00015 g004

Reference Update

The website link of the reference [35] has been updated: https://www.kaggle.com/code/vexxingbanana/brain-mri-image-100-accuracy/notebook, since the original link was incorrect.
The authors state that the scientific conclusions are unaffected. This correction was approved by the Academic Editor. The original publication has also been updated.

Reference

  1. Nayak, D.R.; Padhy, N.; Mallick, P.K.; Bagal, D.K.; Kumar, S. Brain Tumour Classification Using Noble Deep Learning Approach with Parametric Optimization through Metaheuristics Approaches. Computers 2022, 11, 10. [Google Scholar] [CrossRef]
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