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Found 4 papers, 1 papers with code
Visual Instance Retrieval with Deep Convolutional Networks
This paper provides an extensive study on the availability of image representations based on convolutional networks (ConvNets) for the task of visual instance retrieval.
Persistent Evidence of Local Image Properties in Generic ConvNets
Supervised training of a convolutional network for object classification should make explicit any information related to the class of objects and disregard any auxiliary information associated with the capture of the image or the variation within the object class.
Factors of Transferability for a Generic ConvNet Representation
In the common scenario, a ConvNet is trained on a large labeled dataset (source) and the feed-forward units activation of the trained network, at a certain layer of the network, is used as a generic representation of an input image for a task with relatively smaller training set (target).
CNN Features off-the-shelf: an Astounding Baseline for Recognition
We report on a series of experiments conducted for different recognition tasks using the publicly available code and model of the \overfeat network which was trained to perform object classification on ILSVRC13.
