Considerations in Evaluation of Deep Hashing Networks for Information Retrieval System

Subin Kim; Yunseon Choi; Byunghan Lee

doi:10.1109/ISOCC59558.2023.10396568

Considerations in Evaluation of Deep Hashing Networks for Information Retrieval System

Subin Kim
, Yunseon Choi
, Byunghan Lee

Electronic Engineering Program

Seoul National University of Science and Technology (SNUST)

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

Deep hashing is a method utilized in information retrieval systems, involving learning hash functions using deep neural networks. Mean Average Precision (mAP), a popular metric for evaluating hashing models, faces critical challenges in providing reliable performance scores. Despite the development of recent metrics like Mean Local Group Average Precision (mL-GAP) and Radius Aware Mean Average Precision (RAMAP), only a limited number of papers evaluated their hashing algorithms using these metrics. In this paper, we compare the performance of common deep hashing models using various evaluation metrics for precise comparison.

Original language	English
Title of host publication	Proceedings - International SoC Design Conference 2023, ISOCC 2023
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	149-150
Number of pages	2
ISBN (Electronic)	9798350327038
DOIs	https://doi.org/10.1109/ISOCC59558.2023.10396568
State	Published - 2023
Event	20th International SoC Design Conference, ISOCC 2023 - Jeju, Korea, Republic of Duration: 25 Oct 2023 → 28 Oct 2023

Publication series

Name	Proceedings - International SoC Design Conference 2023, ISOCC 2023

Conference

Conference	20th International SoC Design Conference, ISOCC 2023
Country/Territory	Korea, Republic of
City	Jeju
Period	25/10/23 → 28/10/23

Keywords

deep hashing
evaluation metric
information retrieval
representation learning

Access to Document

10.1109/ISOCC59558.2023.10396568

Cite this

Kim, S., Choi, Y., & Lee, B. (2023). Considerations in Evaluation of Deep Hashing Networks for Information Retrieval System. In Proceedings - International SoC Design Conference 2023, ISOCC 2023 (pp. 149-150). (Proceedings - International SoC Design Conference 2023, ISOCC 2023). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ISOCC59558.2023.10396568

@inproceedings{e185194da9cd42379e0fb1637a27297a,

title = "Considerations in Evaluation of Deep Hashing Networks for Information Retrieval System",

abstract = "Deep hashing is a method utilized in information retrieval systems, involving learning hash functions using deep neural networks. Mean Average Precision (mAP), a popular metric for evaluating hashing models, faces critical challenges in providing reliable performance scores. Despite the development of recent metrics like Mean Local Group Average Precision (mL-GAP) and Radius Aware Mean Average Precision (RAMAP), only a limited number of papers evaluated their hashing algorithms using these metrics. In this paper, we compare the performance of common deep hashing models using various evaluation metrics for precise comparison.",

keywords = "deep hashing, evaluation metric, information retrieval, representation learning",

author = "Subin Kim and Yunseon Choi and Byunghan Lee",

note = "Publisher Copyright: {\textcopyright} 2023 IEEE.; 20th International SoC Design Conference, ISOCC 2023 ; Conference date: 25-10-2023 Through 28-10-2023",

year = "2023",

doi = "10.1109/ISOCC59558.2023.10396568",

language = "English",

series = "Proceedings - International SoC Design Conference 2023, ISOCC 2023",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

pages = "149--150",

booktitle = "Proceedings - International SoC Design Conference 2023, ISOCC 2023",

}

Kim, S, Choi, Y & Lee, B 2023, Considerations in Evaluation of Deep Hashing Networks for Information Retrieval System. in Proceedings - International SoC Design Conference 2023, ISOCC 2023. Proceedings - International SoC Design Conference 2023, ISOCC 2023, Institute of Electrical and Electronics Engineers Inc., pp. 149-150, 20th International SoC Design Conference, ISOCC 2023, Jeju, Korea, Republic of, 25/10/23. https://doi.org/10.1109/ISOCC59558.2023.10396568

Considerations in Evaluation of Deep Hashing Networks for Information Retrieval System. / Kim, Subin; Choi, Yunseon; Lee, Byunghan.
Proceedings - International SoC Design Conference 2023, ISOCC 2023. Institute of Electrical and Electronics Engineers Inc., 2023. p. 149-150 (Proceedings - International SoC Design Conference 2023, ISOCC 2023).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Considerations in Evaluation of Deep Hashing Networks for Information Retrieval System

AU - Kim, Subin

AU - Choi, Yunseon

AU - Lee, Byunghan

PY - 2023

Y1 - 2023

N2 - Deep hashing is a method utilized in information retrieval systems, involving learning hash functions using deep neural networks. Mean Average Precision (mAP), a popular metric for evaluating hashing models, faces critical challenges in providing reliable performance scores. Despite the development of recent metrics like Mean Local Group Average Precision (mL-GAP) and Radius Aware Mean Average Precision (RAMAP), only a limited number of papers evaluated their hashing algorithms using these metrics. In this paper, we compare the performance of common deep hashing models using various evaluation metrics for precise comparison.

AB - Deep hashing is a method utilized in information retrieval systems, involving learning hash functions using deep neural networks. Mean Average Precision (mAP), a popular metric for evaluating hashing models, faces critical challenges in providing reliable performance scores. Despite the development of recent metrics like Mean Local Group Average Precision (mL-GAP) and Radius Aware Mean Average Precision (RAMAP), only a limited number of papers evaluated their hashing algorithms using these metrics. In this paper, we compare the performance of common deep hashing models using various evaluation metrics for precise comparison.

KW - deep hashing

KW - evaluation metric

KW - information retrieval

KW - representation learning

UR - https://www.scopus.com/pages/publications/85184810463

U2 - 10.1109/ISOCC59558.2023.10396568

DO - 10.1109/ISOCC59558.2023.10396568

M3 - Conference contribution

AN - SCOPUS:85184810463

T3 - Proceedings - International SoC Design Conference 2023, ISOCC 2023

SP - 149

EP - 150

BT - Proceedings - International SoC Design Conference 2023, ISOCC 2023

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 20th International SoC Design Conference, ISOCC 2023

Y2 - 25 October 2023 through 28 October 2023

ER -

Considerations in Evaluation of Deep Hashing Networks for Information Retrieval System

Abstract

Publication series

Conference

Keywords

Access to Document

Other files and links

Fingerprint

Cite this