Oral cancer is one of the dreadful diseases that affect the people of ages above 40 in most cases. It affects the regions around the mouth especially the back part of mouth which can lead to death often. There are various compu- tational techniques available to detect this widespread disease at the later stage only. If the disease is detected at an earlier stage, then the survival rate of the victims can be increased to 5 years. This paper focuses on detecting oral can- cerous cells at an earlier stage using deep learning techniques as they work ex- tremely well for image recognition and image classification. An intelligent technique comprising of Restricted Boltzmann Machine (RBM) is applied for differentiating the benign and malignant tissue in hyperspectral images (HSI). After experimental results, accuracy obtained was 95.75% using the proposed enhanced RBM technique..
V, K. K., & J, D. V. F. (2021). Detection Of Oral Cancer In Hyperspectral Images Using Restricted Boltzmann Machines. Int. J. of Aquatic Science, 12(3), 1760-1766.
MLA
Kiruthikaa K V; Dr Vijay Franklin J. "Detection Of Oral Cancer In Hyperspectral Images Using Restricted Boltzmann Machines". Int. J. of Aquatic Science, 12, 3, 2021, 1760-1766.
HARVARD
V, K. K., J, D. V. F. (2021). 'Detection Of Oral Cancer In Hyperspectral Images Using Restricted Boltzmann Machines', Int. J. of Aquatic Science, 12(3), pp. 1760-1766.
VANCOUVER
V, K. K., J, D. V. F. Detection Of Oral Cancer In Hyperspectral Images Using Restricted Boltzmann Machines. Int. J. of Aquatic Science, 2021; 12(3): 1760-1766.
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