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Title: :  VITAMIN DEFICIENCY DETECTION USING CONVOLUTIONAL NEURAL NETWORK WITH ADAM OPTIMIZATION
PaperId: :  22832
Published in:   International Journal Of Advance Research And Innovative Ideas In Education
Publisher:   IJARIIE
e-ISSN:   2395-4396
Volume/Issue:    Volume 10 Issue 2 2024
DUI:    16.0415/IJARIIE-22832
Licence: :   IJARIIE is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

Author NameAuthor Institute
Dr N. Durga RaoVasireddy Venkatadri Institute of Technology
K. Shanmuka Sivani SinghVasireddy Venkatadri Institute of Technology
I. ChethanaVasireddy Venkatadri Institute of Technology
M. Uma MadhuriVasireddy Venkatadri Institute of Technology
P. MadhuriVasireddy Venkatadri Institute of Technology

Abstract

Machine Learning
Vitamins, Convolutional neural network, Mean Square Error, Deficiency, Diagnosis
Vitamin deficiency is very common worldwide that causes various types of diseases. Vitamins are an important part of our diet. Without vitamins, a deficiency occurs. In this paper we are introducing Deep Learning CNN model for diagnosing vitamin deficiency at early stage of deficiency. For this we had considered different types of input datasets such as nails, tongue, instead of Blood. In this paper, A wide spectrum of vitamin deficiencies can show one or more visually distinguishable symptoms and indications that appear in multiple locations in the human body. The platform also allows medical experts to assist in improving the range of detection and accuracy of the application through the contribution and verification of visual data of their patients allowing for more refined image analysis and feature extraction capabilities using Deep CNN (Convolutional neural network). Training is performed using a dataset comprising of images of finger nails, Tongue and eyes. Deep Learning is used to classify the images on the basis of color and textures and gives the probable cause for the same. In this proposed method we will develop and effective methodology for detecting vitamin deficiency using Adam optimizer with more accurate results with reduced MSE (Mean Square Error). The testing results of accuracy for all the cases are above 90%. This also shows the performance evaluation metric values are better that many state of art methods. This is a useful methodology for people to overcome a global problem that affects millions of people worldwide mainly as a result of inadequate nutritional awareness, and it will help healthcare workers in the long term in obtaining more accurate diagnoses in a simple way and is also cost effective without pain.

Citations

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IJARIIE Dr N. Durga Rao, K. Shanmuka Sivani Singh, I. Chethana, M. Uma Madhuri, and P. Madhuri. "VITAMIN DEFICIENCY DETECTION USING CONVOLUTIONAL NEURAL NETWORK WITH ADAM OPTIMIZATION" International Journal Of Advance Research And Innovative Ideas In Education Volume 10 Issue 2 2024 Page 855-862
MLA Dr N. Durga Rao, K. Shanmuka Sivani Singh, I. Chethana, M. Uma Madhuri, and P. Madhuri. "VITAMIN DEFICIENCY DETECTION USING CONVOLUTIONAL NEURAL NETWORK WITH ADAM OPTIMIZATION." International Journal Of Advance Research And Innovative Ideas In Education 10.2(2024) : 855-862.
APA Dr N. Durga Rao, K. Shanmuka Sivani Singh, I. Chethana, M. Uma Madhuri, & P. Madhuri. (2024). VITAMIN DEFICIENCY DETECTION USING CONVOLUTIONAL NEURAL NETWORK WITH ADAM OPTIMIZATION. International Journal Of Advance Research And Innovative Ideas In Education, 10(2), 855-862.
Chicago Dr N. Durga Rao, K. Shanmuka Sivani Singh, I. Chethana, M. Uma Madhuri, and P. Madhuri. "VITAMIN DEFICIENCY DETECTION USING CONVOLUTIONAL NEURAL NETWORK WITH ADAM OPTIMIZATION." International Journal Of Advance Research And Innovative Ideas In Education 10, no. 2 (2024) : 855-862.
Oxford Dr N. Durga Rao, K. Shanmuka Sivani Singh, I. Chethana, M. Uma Madhuri, and P. Madhuri. 'VITAMIN DEFICIENCY DETECTION USING CONVOLUTIONAL NEURAL NETWORK WITH ADAM OPTIMIZATION', International Journal Of Advance Research And Innovative Ideas In Education, vol. 10, no. 2, 2024, p. 855-862. Available from IJARIIE, https://ijariie.com/AdminUploadPdf/VITAMIN_DEFICIENCY_DETECTION_USING_CONVOLUTIONAL_NEURAL_NETWORK_WITH_ADAM_OPTIMIZATION_ijariie22832.pdf (Accessed : 27 April 2024).
Harvard Dr N. Durga Rao, K. Shanmuka Sivani Singh, I. Chethana, M. Uma Madhuri, and P. Madhuri. (2024) 'VITAMIN DEFICIENCY DETECTION USING CONVOLUTIONAL NEURAL NETWORK WITH ADAM OPTIMIZATION', International Journal Of Advance Research And Innovative Ideas In Education, 10(2), pp. 855-862IJARIIE [Online]. Available at: https://ijariie.com/AdminUploadPdf/VITAMIN_DEFICIENCY_DETECTION_USING_CONVOLUTIONAL_NEURAL_NETWORK_WITH_ADAM_OPTIMIZATION_ijariie22832.pdf (Accessed : 27 April 2024)
IEEE Dr N. Durga Rao, K. Shanmuka Sivani Singh, I. Chethana, M. Uma Madhuri, and P. Madhuri, "VITAMIN DEFICIENCY DETECTION USING CONVOLUTIONAL NEURAL NETWORK WITH ADAM OPTIMIZATION," International Journal Of Advance Research And Innovative Ideas In Education, vol. 10, no. 2, pp. 855-862, Mar-App 2024. [Online]. Available: https://ijariie.com/AdminUploadPdf/VITAMIN_DEFICIENCY_DETECTION_USING_CONVOLUTIONAL_NEURAL_NETWORK_WITH_ADAM_OPTIMIZATION_ijariie22832.pdf [Accessed : 27 April 2024].
Turabian Dr N. Durga Rao, K. Shanmuka Sivani Singh, I. Chethana, M. Uma Madhuri, and P. Madhuri. "VITAMIN DEFICIENCY DETECTION USING CONVOLUTIONAL NEURAL NETWORK WITH ADAM OPTIMIZATION." International Journal Of Advance Research And Innovative Ideas In Education [Online]. volume 10 number 2 (27 April 2024).
Vancouver Dr N. Durga Rao, K. Shanmuka Sivani Singh, I. Chethana, M. Uma Madhuri, and P. Madhuri. VITAMIN DEFICIENCY DETECTION USING CONVOLUTIONAL NEURAL NETWORK WITH ADAM OPTIMIZATION. International Journal Of Advance Research And Innovative Ideas In Education [Internet]. 2024 [Cited : 27 April 2024]; 10(2) : 855-862. Available from: https://ijariie.com/AdminUploadPdf/VITAMIN_DEFICIENCY_DETECTION_USING_CONVOLUTIONAL_NEURAL_NETWORK_WITH_ADAM_OPTIMIZATION_ijariie22832.pdf
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