TY - GEN
T1 - Machine learning aided classification and grading of biopsy sample using discrete wavelet transform and gray level co-occurrence matrix
AU - Sindhoora, K. M.
AU - Spandana, K. U.
AU - Raghavendra, U.
AU - Rai, Sharada
AU - Mahato, K. K.
AU - Mazumder, Nirmal
N1 - Funding Information:
This work is supported by Department of Science and Technology (DST) (Project No.: GITA/DST/TWN/P-95/2021) and Science and Engineering Research Board (SERB) (Project No.: MTR/2020/000058), Gov. of India, India. We thank Manipal School of Life Sciences (MSLS), Manipal Academy of Higher Education (MAHE), Manipal, India for providing the infrastructure and facilities. Ms. Sindhoora thank MAHE, Manipal, India for the Dr. T.M.A. Pai Ph.D. fellowship.
Publisher Copyright:
© 2022 The Author(s)
PY - 2022
Y1 - 2022
N2 - Machine learning based classification and grading of the pathological specimen plays an important role in the biomedical field. In the current study, we discuss the importance of feature extraction for machine learning.
AB - Machine learning based classification and grading of the pathological specimen plays an important role in the biomedical field. In the current study, we discuss the importance of feature extraction for machine learning.
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M3 - Conference contribution
AN - SCOPUS:85146825588
T3 - Optics InfoBase Conference Papers
BT - Frontiers in Optics, FiO 2022
PB - Optica Publishing Group (formerly OSA)
T2 - Frontiers in Optics, FiO 2022
Y2 - 17 October 2022 through 20 October 2022
ER -