Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Optimized Feature Space Learning for Generating Efficient Binary Codes
  for Image Retrieval   In this paper we propose an approach for learning low dimensional optimized
feature space with minimum intra-class variance and maximum inter-class
variance. We address the problem of high-dimensionality of feature vectors
extracted from neural networks by taking care of the global statistics of
feature space. Classical approach of Linear Discriminant Analysis (LDA) is
generally used for generating an optimized low dimensional feature space for
single-labeled images. Since, image retrieval involves both multi-labeled and
single-labeled images, we utilize the equivalence between LDA and Canonical
Correlation Analysis (CCA) to generate an optimized feature space for
single-labeled images and use CCA to generate an optimized feature space for
multi-labeled images. Our approach correlates the projections of feature
vectors with label vectors in our CCA based network architecture. The neural
network minimize a loss function which maximizes the correlation coefficients.
We binarize our generated feature vectors with the popular Iterative
Quantization (ITQ) approach and also propose an ensemble network to generate
binary codes of desired bit length for image retrieval. Our measurement of mean
average precision shows competitive results on other state-of-the-art
single-labeled and multi-labeled image retrieval datasets.

29
The categories of this paper are: funct-an
31
The categories of this paper are: ao-sci
5
The categories of this paper are: gr-qc
6
The categories of this paper are: astro-ph
4
The categories of this paper are: cond-mat
34
The categories of this paper are: chem-ph
28
The categories of this paper are: alg-geom
16
The categories of this paper are: stat
10
The categories of this paper are: q-bio
8
The categories of this paper are: hep-ex
17
The categories of this paper are: q-fin
30
The categories of this paper are: q-alg
11
The categories of this paper are: hep-lat
2
The categories of this paper are: math
35
The categories of this paper are: mtrl-th
9
The categories of this paper are: nlin