International Journal of Scientific and Research Publications

IJSRP, Volume 9, Issue 10, October 2019 Edition [ISSN 2250-3153]


Transfer learning using VGG-16 with Deep Convolutional Neural Network for Classifying Images
      Srikanth Tammina
Abstract: Traditionally, data mining algorithms and machine learning algorithms are engineered to approach the problems in isolation. These algorithms are employed to train the model in separation on a specific feature space and same distribution. Depending on the business case, a model is trained by applying a machine learning algorithm for a specific task. A widespread assumption in the field of machine learning is that training data and test data must have identical feature spaces with the underlying distribution. On the contrary, in real world this assumption may not hold and thus models need to be rebuilt from the scratch if features and distribution changes.

Reference this Research Paper (copy & paste below code):

Srikanth Tammina (2019); Transfer learning using VGG-16 with Deep Convolutional Neural Network for Classifying Images; International Journal of Scientific and Research Publications (IJSRP) 9(10) (ISSN: 2250-3153), DOI: http://dx.doi.org/10.29322/IJSRP.9.10.2019.p9420
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