machine learning - how to handle text and image input together in neural network algorithm -


i working on cnn machine learning algorithm sample in tensorflow. know input feature in image format. there possibility handle text & image input in cnn or using other machine learning algoritm. how make sense of output.

yes, possible handle text , image data together. feature vectors created using each text data-point or image data-point can combined , used in parallel new big feature vector. after vectorization of text data, there not difference between pixel vectors , text vectors.

specifically in case of cnn, final model, combined neural network can created has convolutional branch 1 on side while vectorized words branch on other side.

here image illustrates same

image credits: this image christopher bonnett's article

for more details, please refer above mentioned article. has explained how e-commerce products can classified various category hierarchies using both image , text data.


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