finetuning

Fine-Tuning ImageNet model for Classification

What am I doing today? I have installed caffe and the required libraries using this really good guide. The aim of my experiment is to fine-tune tha VGG-16 network for classification. The VGG-16 network I use is pre-trained on ImageNet for classification. I will exploit it’s caffemodel to fine-tune the weights for my own purpose. Data-Preparation Getting the data prepared correctly finishes most of your work. Step 1- Go to caffe/data folder and create your own data folder there....

Fine-tuning pre-trained VGG Face convolutional neural networks model for regression with Caffe

Task: Use a pre-trained face descriptor model to output a single continuous variable predicting an outcome using Caffe’s CNN implementation. Picture Reference: https://deeplearning4j.org/linear-regression So, we’re going to take VGG-Face (a model that is pre-trained on Facial Images) and train this model to predict the salary of the person. This sounds daft! How can anyone predict a person’s salary simply by looking at a person’s face? You and I cannot do this....