Deep Learning of Binary Hash Codes CIFAR10

Deep Learning of Binary Hash Codes for Fast Image Retrieval

name: Deep Binary Hash Codes CIFAR10

caffemodel: KevinNet_CIFAR10_48.caffemodel

caffemodel_url: https://www.dropbox.com/s/1om7xa8mz93wkzh/KevinNet_CIFAR10_48.caffemodel?d

gist_id: 266d4150a1db5810398e

##GitHub

Download our model and source code here: https://github.com/kevinlin311tw/caffe-cvprw15

##Description

This model is a replication of the model described in the paper: http://www.iis.sinica.edu.tw/~kevinlin311.tw/cvprw15.pdf

The model is the iteration 50,000 snapshot trained on CIFAR-10.

The number of neurons in the latent layer is 48, in order to learn 48 bits binary hash codes.

License

The data used to train this model comes from the ImageNet project, which distributes its database to researchers who agree to a following term of access: "Researcher shall use the Database only for non-commercial research and educational purposes." Accordingly, this model is distributed under a non-commercial license.