Leveraging computer vision and natural language processing for efficient metadata extraction in digitized books

Authors

Institutions

Publication Details

Journal
International Journal of Pervasive Computing and Communications
Published
2026-08-24
DOI
https://doi.org/10.1108/ijpcc-02-2025-0077
Primary Topic
Handwritten Text Recognition Techniques
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Leveraging computer vision and natural language processing for efficient metadata extraction in digitized books

Amalia Amalia, Khairul Imam, Baihaqi Siregar
International Journal of Pervasive Computing and Communications
Handwritten Text Recognition Techniques
article

Leveraging computer vision and natural language processing for efficient metadata extraction in digitized books

Amalia Amalia, Khairul Imam, Baihaqi Siregar
article en

Abstract

No abstract available for this paper.
International Journal of Pervasive Computing and Communications
Universitas Sumatera Utara (ID)
Quality Education
Openalex Percentile: Top 12%
Handwritten Text Recognition Techniques
DOISourceOpenAlex
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.