Mixed data through multiple input for price prediction with multilayer perception and mini VGG net

Abstract

The multi-input with mixed data modality of the model is based on three folded structure. The first input model is structured by Convolution Network that accepts the images related to the house. The implementation of the network is miniVGGNet design. The network is tested among, which gives a better outcome. The output valued is concatenated eventuall y with numerical value entry of the same set which is trained and processed by multi-layer perceptron for review the house price of the building. The linear activation is helped to evaluate the predicted value of price after equal dimension merging of convolutional and multi-layer perceptron network.