Search Results for author: Ali Sharif Razavian

Found 4 papers, 1 papers with code

Visual Instance Retrieval with Deep Convolutional Networks

no code implementations20 Dec 2014 Ali Sharif Razavian, Josephine Sullivan, Stefan Carlsson, Atsuto Maki

This paper provides an extensive study on the availability of image representations based on convolutional networks (ConvNets) for the task of visual instance retrieval.

Image Retrieval

Persistent Evidence of Local Image Properties in Generic ConvNets

no code implementations24 Nov 2014 Ali Sharif Razavian, Hossein Azizpour, Atsuto Maki, Josephine Sullivan, Carl Henrik Ek, Stefan Carlsson

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.

General Classification

Factors of Transferability for a Generic ConvNet Representation

no code implementations22 Jun 2014 Hossein Azizpour, Ali Sharif Razavian, Josephine Sullivan, Atsuto Maki, Stefan Carlsson

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).

Dimensionality Reduction Representation Learning

CNN Features off-the-shelf: an Astounding Baseline for Recognition

4 code implementations23 Mar 2014 Ali Sharif Razavian, Hossein Azizpour, Josephine Sullivan, Stefan Carlsson

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.

General Classification Image Classification +2

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