Deepa, B. G., & Senthil, S. (2022). Predicting invasive ductal carcinoma tissues in whole slide images of breast Cancer by using convolutional neural network model and multiple classifiers. Multimedia Tools and Applications: An International Journal, 81(6), 8575-8596. https://doi.org/10.1007/s11042-022-12114-9
ISO-690 (author-date, English)DEEPA, B. G. und SENTHIL, S., 2022. Predicting invasive ductal carcinoma tissues in whole slide images of breast Cancer by using convolutional neural network model and multiple classifiers. Multimedia Tools and Applications: An International Journal. 1 März 2022. Vol. 81, no. 6, p. 8575-8596. DOI 10.1007/s11042-022-12114-9.
Modern Language Association 9th editionDeepa, B. G., und S. Senthil. „Predicting Invasive Ductal Carcinoma Tissues in Whole Slide Images of Breast Cancer by Using Convolutional Neural Network Model and Multiple Classifiers“. Multimedia Tools and Applications: An International Journal, Bd. 81, Nr. 6, März 2022, S. 8575-96, https://doi.org/10.1007/s11042-022-12114-9.
Mohr Siebeck - Recht (Deutsch - Österreich)Deepa, B. G./Senthil, S.: Predicting invasive ductal carcinoma tissues in whole slide images of breast Cancer by using convolutional neural network model and multiple classifiers, Multimedia Tools and Applications: An International Journal 2022, 8575-8596.
Emerald - HarvardDeepa, B.G. und Senthil, S. (2022), „Predicting invasive ductal carcinoma tissues in whole slide images of breast Cancer by using convolutional neural network model and multiple classifiers“, Multimedia Tools and Applications: An International Journal, Vol. 81 No. 6, S. 8575-8596.