TUTCRIS - Tampereen teknillinen yliopisto

TUTCRIS

Deep p-Fibonacci scattering networks

Tutkimustuotosvertaisarvioitu

Yksityiskohdat

AlkuperäiskieliEnglanti
OtsikkoElectronic Imaging
AlaotsikkoImage Processing: Algorithms and Systems XVI
KustantajaSociety for Imaging Science and Technology
DOI - pysyväislinkit
TilaJulkaistu - 2018
OKM-julkaisutyyppiA4 Artikkeli konferenssijulkaisussa
TapahtumaIS&T International Symposium on Electronic Imaging -
Kesto: 28 tammikuuta 20182 helmikuuta 2018

Julkaisusarja

Nimi
ISSN (elektroninen)2470-1173

Conference

ConferenceIS&T International Symposium on Electronic Imaging
Ajanjakso28/01/182/02/18

Tiivistelmä

Recently, the use of neural networks for image classification has become widely spread. Thanks to the availability of increased computational power, better performing architectures have been designed, such as the Deep Neural networks. In this work, we propose a novel image representation framework exploiting the Deep p- Fibonacci scattering network. The architecture is based on the structured p-Fibonacci scattering over graph data. This approach allows to provide good accuracy in classification while reducing the computational complexity. Experimental results demonstrate that the performance of the proposed method is comparable to state-of-the-art unsupervised methods while being computationally more efficient.