@InProceedings{SantosPont:2019:AlLoGl,
author = "Santos, Fernando Pereira dos and Ponti, Moacir Antonelli",
affiliation = "{Universidade de S{\~a}o Paulo} and {Universidade de S{\~a}o
Paulo}",
title = "Alignment of Local and Global Features from Multiple Layers of
Convolutional Neural Network for Image Classification",
booktitle = "Proceedings...",
year = "2019",
editor = "Oliveira, Luciano Rebou{\c{c}}as de and Sarder, Pinaki and Lage,
Marcos and Sadlo, Filip",
organization = "Conference on Graphics, Patterns and Images, 32. (SIBGRAPI)",
publisher = "IEEE Computer Society",
address = "Los Alamitos",
keywords = "feature learning, convolutional networks, fusion multiple maps,
manifold alignment.",
abstract = "Convolutional networks have been extensively applied to obtain
features spaces for classification tasks. Although those achieve
high accuracy in many scenarios, typically only the top layers of
the network are explored. Hence, a relevant question arises from
this fact: are initial layers useful in terms of discriminative
ability? In this paper, we leverage the complementary description
offered by such first layers. Our method consists of features
extraction in multiple layers, followed by feature selection,
fusion of feature maps from the different layers, and space
alignment. Through an extensive experimentation with different
datasets and studying different training strategies, our results
show that local information, coming from the first layers, may
significantly improve the classification performance when merged
with a global descriptor extracted from a top layer of the
network. We report different methods for reducing the
dimensionality of the local descriptors, and guidelines on how to
align them so that to perform fusion. Our study encourages future
studies on combining feature maps from multiple layers, which may
be relevant in particular for transfer learning scenarios.",
conference-location = "Rio de Janeiro, RJ, Brazil",
conference-year = "28-31 Oct. 2019",
doi = "10.1109/SIBGRAPI.2019.00040",
url = "http://dx.doi.org/10.1109/SIBGRAPI.2019.00040",
language = "en",
ibi = "8JMKD3MGPEW34M/3U2JCS5",
url = "http://urlib.net/ibi/8JMKD3MGPEW34M/3U2JCS5",
targetfile = "camera_ready_92.pdf",
urlaccessdate = "2024, Apr. 28"
}