TUTCRIS - Tampereen teknillinen yliopisto

TUTCRIS

Self-Organizing Binary Encoding for Approximate Nearest Neighbor Search

Tutkimustuotosvertaisarvioitu

Yksityiskohdat

AlkuperäiskieliEnglanti
Otsikko2016 24th European Signal Processing Conference (EUSIPCO)
KustantajaIEEE
Sivut1103-1107
Sivumäärä5
ISBN (painettu)978-0-9928-6265-7
TilaJulkaistu - 2016
OKM-julkaisutyyppiA4 Artikkeli konferenssijulkaisussa
TapahtumaEUROPEAN SIGNAL PROCESSING CONFERENCE -
Kesto: 1 tammikuuta 1900 → …

Julkaisusarja

Nimi
ISSN (elektroninen)2076-1465

Conference

ConferenceEUROPEAN SIGNAL PROCESSING CONFERENCE
Ajanjakso1/01/00 → …

Tiivistelmä

Approximate Nearest Neighbor (ANN) search for indexing and retrieval has become very popular with the recent growth of the databases in both size and dimension. In this paper, we propose a novel method for fast approximate distance calculation among the compressed samples. Inspiring from Kohonen’s self-organizing maps, we propose a structured hierarchical quantization scheme in order to compress database samples in a more efficient way. Moreover, we introduce an error correction stage for encoding, which further improves the
performance of the proposed method. The results on publicly available benchmark datasets demonstrate that the proposed method outperforms many well-known methods with comparable computational cost and storage space.

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