Real-Time Detection of Cracks on Concrete Bridge Decks Using Deep Learning in the Frequency Domain Article Swipe

View

Qianyun Zhang , Kaveh Barri , Saeed Babanajad , Amir H. Alavi ·

YOU? · · 2020 · Open Access · · DOI: https://doi.org/10.1016/j.eng.2020.07.026

This paper presents a vision-based crack detection approach for concrete bridge decks using an integrated one-dimensional convolutional neural network (1D-CNN) and long short-term memory (LSTM) method in the image frequency domain. The so-called 1D-CNN-LSTM algorithm is trained using thousands of images of cracked and non-cracked concrete bridge decks. In order to improve the training efficiency, images are first transformed into the frequency domain during a preprocessing phase. The algorithm is then calibrated using the flattened frequency data. LSTM is used to improve the performance of the developed network for long sequence data. The accuracy of the developed model is 99.05%, 98.9%, and 99.25%, respectively, for training, validation, and testing data. An implementation framework is further developed for future application of the trained model for large-scale images. The proposed 1D-CNN-LSTM method exhibits superior performance in comparison with existing deep learning methods in terms of accuracy and computation time. The fast implementation of the 1D-CNN-LSTM algorithm makes it a promising tool for real-time crack detection.

Related Topics

Computer Science

Convolutional Neural Network

Artificial Intelligence

Mathematical Analysis

Concepts

Computer science Convolutional neural network Preprocessor Bridge (graph theory) Artificial intelligence Frequency domain Deep learning Time domain Domain (mathematical analysis) Computation Data pre-processing Image (mathematics) Artificial neural network Pattern recognition (psychology) Algorithm Computer vision Medicine Internal medicine Mathematics Mathematical analysis

Metadata

Type: article
Language: en
Landing Page: https://doi.org/10.1016/j.eng.2020.07.026
OA Status: gold
Cited By: 130
References: 58
Related Works: 10
OpenAlex ID: https://openalex.org/W3098048737

All OpenAlex metadata

Raw OpenAlex JSON

OpenAlex ID: https://openalex.org/W3098048737

Canonical identifier for this work in OpenAlex
DOI: https://doi.org/10.1016/j.eng.2020.07.026

Digital Object Identifier
Title: Real-Time Detection of Cracks on Concrete Bridge Decks Using Deep Learning in the Frequency Domain

Work title
Type: article

OpenAlex work type
Language: en

Primary language
Publication year: 2020

Year of publication
Publication date: 2020-11-19

Full publication date if available
Authors: Qianyun Zhang, Kaveh Barri, Saeed Babanajad, Amir H. Alavi

List of authors in order
Landing page: https://doi.org/10.1016/j.eng.2020.07.026

Publisher landing page
Open access: Yes

Whether a free full text is available
OA status: gold

Open access status per OpenAlex
OA URL: https://doi.org/10.1016/j.eng.2020.07.026

Direct OA link when available
Concepts: Computer science, Convolutional neural network, Preprocessor, Bridge (graph theory), Artificial intelligence, Frequency domain, Deep learning, Time domain, Domain (mathematical analysis), Computation, Data pre-processing, Image (mathematics), Artificial neural network, Pattern recognition (psychology), Algorithm, Computer vision, Medicine, Internal medicine, Mathematics, Mathematical analysis

Top concepts (fields/topics) attached by OpenAlex
Cited by: 130

Total citation count in OpenAlex
Citations by year (recent): 2025: 30, 2024: 33, 2023: 34, 2022: 25, 2021: 8

Per-year citation counts (last 5 years)
References (count): 58

Number of works referenced by this work
Related works (count): 10

Other works algorithmically related by OpenAlex

Full payload

id	https://openalex.org/W3098048737
doi	https://doi.org/10.1016/j.eng.2020.07.026
ids.doi	https://doi.org/10.1016/j.eng.2020.07.026
ids.mag	3098048737
ids.openalex	https://openalex.org/W3098048737
fwci	9.88063356
type	article
title	Real-Time Detection of Cracks on Concrete Bridge Decks Using Deep Learning in the Frequency Domain
biblio.issue	12
biblio.volume	7
biblio.last_page	1796
biblio.first_page	1786
topics[0].id	https://openalex.org/T11606
topics[0].field.id	https://openalex.org/fields/22
topics[0].field.display_name	Engineering
topics[0].score	1.0
topics[0].domain.id	https://openalex.org/domains/3
topics[0].domain.display_name	Physical Sciences
topics[0].subfield.id	https://openalex.org/subfields/2205
topics[0].subfield.display_name	Civil and Structural Engineering
topics[0].display_name	Infrastructure Maintenance and Monitoring
topics[1].id	https://openalex.org/T11850
topics[1].field.id	https://openalex.org/fields/22
topics[1].field.display_name	Engineering
topics[1].score	0.9919999837875366
topics[1].domain.id	https://openalex.org/domains/3
topics[1].domain.display_name	Physical Sciences
topics[1].subfield.id	https://openalex.org/subfields/2205
topics[1].subfield.display_name	Civil and Structural Engineering
topics[1].display_name	Concrete Corrosion and Durability
topics[2].id	https://openalex.org/T10534
topics[2].field.id	https://openalex.org/fields/22
topics[2].field.display_name	Engineering
topics[2].score	0.9908999800682068
topics[2].domain.id	https://openalex.org/domains/3
topics[2].domain.display_name	Physical Sciences
topics[2].subfield.id	https://openalex.org/subfields/2205
topics[2].subfield.display_name	Civil and Structural Engineering
topics[2].display_name	Structural Health Monitoring Techniques
funders[0].id	https://openalex.org/F4320308115
funders[0].ror	https://ror.org/02j0q7e02
funders[0].display_name	Pennsylvania Department of Transportation
funders[1].id	https://openalex.org/F4320310174
funders[1].ror	https://ror.org/01an3r305
funders[1].display_name	University of Pittsburgh
is_xpac	False
apc_list.value	1000
apc_list.currency	USD
apc_list.value_usd	1000
apc_paid.value	1000
apc_paid.currency	USD
apc_paid.value_usd	1000
concepts[0].id	https://openalex.org/C41008148
concepts[0].level	0
concepts[0].score	0.7710255980491638
concepts[0].wikidata	https://www.wikidata.org/wiki/Q21198
concepts[0].display_name	Computer science
concepts[1].id	https://openalex.org/C81363708
concepts[1].level	2
concepts[1].score	0.7606761455535889
concepts[1].wikidata	https://www.wikidata.org/wiki/Q17084460
concepts[1].display_name	Convolutional neural network
concepts[2].id	https://openalex.org/C34736171
concepts[2].level	2
concepts[2].score	0.7401334047317505
concepts[2].wikidata	https://www.wikidata.org/wiki/Q918333
concepts[2].display_name	Preprocessor
concepts[3].id	https://openalex.org/C100776233
concepts[3].level	2
concepts[3].score	0.7142071723937988
concepts[3].wikidata	https://www.wikidata.org/wiki/Q2532492
concepts[3].display_name	Bridge (graph theory)
concepts[4].id	https://openalex.org/C154945302
concepts[4].level	1
concepts[4].score	0.6032735109329224
concepts[4].wikidata	https://www.wikidata.org/wiki/Q11660
concepts[4].display_name	Artificial intelligence
concepts[5].id	https://openalex.org/C19118579
concepts[5].level	2
concepts[5].score	0.5853122472763062
concepts[5].wikidata	https://www.wikidata.org/wiki/Q786423
concepts[5].display_name	Frequency domain
concepts[6].id	https://openalex.org/C108583219
concepts[6].level	2
concepts[6].score	0.5490435361862183
concepts[6].wikidata	https://www.wikidata.org/wiki/Q197536
concepts[6].display_name	Deep learning
concepts[7].id	https://openalex.org/C103824480
concepts[7].level	2
concepts[7].score	0.5400756597518921
concepts[7].wikidata	https://www.wikidata.org/wiki/Q185889
concepts[7].display_name	Time domain
concepts[8].id	https://openalex.org/C36503486
concepts[8].level	2
concepts[8].score	0.5343538522720337
concepts[8].wikidata	https://www.wikidata.org/wiki/Q11235244
concepts[8].display_name	Domain (mathematical analysis)
concepts[9].id	https://openalex.org/C45374587
concepts[9].level	2
concepts[9].score	0.5275188088417053
concepts[9].wikidata	https://www.wikidata.org/wiki/Q12525525
concepts[9].display_name	Computation
concepts[10].id	https://openalex.org/C10551718
concepts[10].level	2
concepts[10].score	0.46105706691741943
concepts[10].wikidata	https://www.wikidata.org/wiki/Q5227332
concepts[10].display_name	Data pre-processing
concepts[11].id	https://openalex.org/C115961682
concepts[11].level	2
concepts[11].score	0.4495224356651306
concepts[11].wikidata	https://www.wikidata.org/wiki/Q860623
concepts[11].display_name	Image (mathematics)
concepts[12].id	https://openalex.org/C50644808
concepts[12].level	2
concepts[12].score	0.4370267391204834
concepts[12].wikidata	https://www.wikidata.org/wiki/Q192776
concepts[12].display_name	Artificial neural network
concepts[13].id	https://openalex.org/C153180895
concepts[13].level	2
concepts[13].score	0.4067772924900055
concepts[13].wikidata	https://www.wikidata.org/wiki/Q7148389
concepts[13].display_name	Pattern recognition (psychology)
concepts[14].id	https://openalex.org/C11413529
concepts[14].level	1
concepts[14].score	0.293485164642334
concepts[14].wikidata	https://www.wikidata.org/wiki/Q8366
concepts[14].display_name	Algorithm
concepts[15].id	https://openalex.org/C31972630
concepts[15].level	1
concepts[15].score	0.26942676305770874
concepts[15].wikidata	https://www.wikidata.org/wiki/Q844240
concepts[15].display_name	Computer vision
concepts[16].id	https://openalex.org/C71924100
concepts[16].level	0
concepts[16].score	0.0
concepts[16].wikidata	https://www.wikidata.org/wiki/Q11190
concepts[16].display_name	Medicine
concepts[17].id	https://openalex.org/C126322002
concepts[17].level	1
concepts[17].score	0.0
concepts[17].wikidata	https://www.wikidata.org/wiki/Q11180
concepts[17].display_name	Internal medicine
concepts[18].id	https://openalex.org/C33923547
concepts[18].level	0
concepts[18].score	0.0
concepts[18].wikidata	https://www.wikidata.org/wiki/Q395
concepts[18].display_name	Mathematics
concepts[19].id	https://openalex.org/C134306372
concepts[19].level	1
concepts[19].score	0.0
concepts[19].wikidata	https://www.wikidata.org/wiki/Q7754
concepts[19].display_name	Mathematical analysis
keywords[0].id	https://openalex.org/keywords/computer-science
keywords[0].score	0.7710255980491638
keywords[0].display_name	Computer science
keywords[1].id	https://openalex.org/keywords/convolutional-neural-network
keywords[1].score	0.7606761455535889
keywords[1].display_name	Convolutional neural network
keywords[2].id	https://openalex.org/keywords/preprocessor
keywords[2].score	0.7401334047317505
keywords[2].display_name	Preprocessor
keywords[3].id	https://openalex.org/keywords/bridge
keywords[3].score	0.7142071723937988
keywords[3].display_name	Bridge (graph theory)
keywords[4].id	https://openalex.org/keywords/artificial-intelligence
keywords[4].score	0.6032735109329224
keywords[4].display_name	Artificial intelligence
keywords[5].id	https://openalex.org/keywords/frequency-domain
keywords[5].score	0.5853122472763062
keywords[5].display_name	Frequency domain
keywords[6].id	https://openalex.org/keywords/deep-learning
keywords[6].score	0.5490435361862183
keywords[6].display_name	Deep learning
keywords[7].id	https://openalex.org/keywords/time-domain
keywords[7].score	0.5400756597518921
keywords[7].display_name	Time domain
keywords[8].id	https://openalex.org/keywords/domain
keywords[8].score	0.5343538522720337
keywords[8].display_name	Domain (mathematical analysis)
keywords[9].id	https://openalex.org/keywords/computation
keywords[9].score	0.5275188088417053
keywords[9].display_name	Computation
keywords[10].id	https://openalex.org/keywords/data-pre-processing
keywords[10].score	0.46105706691741943
keywords[10].display_name	Data pre-processing
keywords[11].id	https://openalex.org/keywords/image
keywords[11].score	0.4495224356651306
keywords[11].display_name	Image (mathematics)
keywords[12].id	https://openalex.org/keywords/artificial-neural-network
keywords[12].score	0.4370267391204834
keywords[12].display_name	Artificial neural network
keywords[13].id	https://openalex.org/keywords/pattern-recognition
keywords[13].score	0.4067772924900055
keywords[13].display_name	Pattern recognition (psychology)
keywords[14].id	https://openalex.org/keywords/algorithm
keywords[14].score	0.293485164642334
keywords[14].display_name	Algorithm
keywords[15].id	https://openalex.org/keywords/computer-vision
keywords[15].score	0.26942676305770874
keywords[15].display_name	Computer vision
language	en
locations[0].id	doi:10.1016/j.eng.2020.07.026
locations[0].is_oa	True
locations[0].source.id	https://openalex.org/S4210192142
locations[0].source.issn	2095-8099, 2096-0026
locations[0].source.type	journal
locations[0].source.is_oa	True
locations[0].source.issn_l	2095-8099
locations[0].source.is_core	True
locations[0].source.is_in_doaj	True
locations[0].source.display_name	Engineering
locations[0].source.host_organization	https://openalex.org/P4310320990
locations[0].source.host_organization_name	Elsevier BV
locations[0].source.host_organization_lineage	https://openalex.org/P4310320990
locations[0].source.host_organization_lineage_names	Elsevier BV
locations[0].license	cc-by-nc-nd
locations[0].pdf_url
locations[0].version	publishedVersion
locations[0].raw_type	journal-article
locations[0].license_id	https://openalex.org/licenses/cc-by-nc-nd
locations[0].is_accepted	True
locations[0].is_published	True
locations[0].raw_source_name	Engineering
locations[0].landing_page_url	https://doi.org/10.1016/j.eng.2020.07.026
indexed_in	crossref, doaj
authorships[0].author.id	https://openalex.org/A5052563154
authorships[0].author.orcid	https://orcid.org/0000-0002-2147-4059
authorships[0].author.display_name	Qianyun Zhang
authorships[0].countries	US
authorships[0].affiliations[0].institution_ids	https://openalex.org/I170201317
authorships[0].affiliations[0].raw_affiliation_string	Department of Civil and Environmental Engineering, University of Pittsburgh, Pittsburgh, PA 15261, USA
authorships[0].institutions[0].id	https://openalex.org/I170201317
authorships[0].institutions[0].ror	https://ror.org/01an3r305
authorships[0].institutions[0].type	education
authorships[0].institutions[0].lineage	https://openalex.org/I170201317
authorships[0].institutions[0].country_code	US
authorships[0].institutions[0].display_name	University of Pittsburgh
authorships[0].author_position	first
authorships[0].raw_author_name	Qianyun Zhang
authorships[0].is_corresponding	False
authorships[0].raw_affiliation_strings	Department of Civil and Environmental Engineering, University of Pittsburgh, Pittsburgh, PA 15261, USA
authorships[1].author.id	https://openalex.org/A5058973510
authorships[1].author.orcid	https://orcid.org/0000-0003-4279-9730
authorships[1].author.display_name	Kaveh Barri
authorships[1].countries	US
authorships[1].affiliations[0].institution_ids	https://openalex.org/I170201317
authorships[1].affiliations[0].raw_affiliation_string	Department of Civil and Environmental Engineering, University of Pittsburgh, Pittsburgh, PA 15261, USA
authorships[1].institutions[0].id	https://openalex.org/I170201317
authorships[1].institutions[0].ror	https://ror.org/01an3r305
authorships[1].institutions[0].type	education
authorships[1].institutions[0].lineage	https://openalex.org/I170201317
authorships[1].institutions[0].country_code	US
authorships[1].institutions[0].display_name	University of Pittsburgh
authorships[1].author_position	middle
authorships[1].raw_author_name	Kaveh Barri
authorships[1].is_corresponding	False
authorships[1].raw_affiliation_strings	Department of Civil and Environmental Engineering, University of Pittsburgh, Pittsburgh, PA 15261, USA
authorships[2].author.id	https://openalex.org/A5024535634
authorships[2].author.orcid
authorships[2].author.display_name	Saeed Babanajad
authorships[2].countries	US
authorships[2].affiliations[0].institution_ids	https://openalex.org/I883842289
authorships[2].affiliations[0].raw_affiliation_string	Wiss, Janney, Elstner Associates Inc., Northbrook, IL 60062, USA
authorships[2].institutions[0].id	https://openalex.org/I883842289
authorships[2].institutions[0].ror	https://ror.org/05eer5n81
authorships[2].institutions[0].type	company
authorships[2].institutions[0].lineage	https://openalex.org/I883842289
authorships[2].institutions[0].country_code	US
authorships[2].institutions[0].display_name	Wiss Janney Elstner Associates
authorships[2].author_position	middle
authorships[2].raw_author_name	Saeed K. Babanajad
authorships[2].is_corresponding	False
authorships[2].raw_affiliation_strings	Wiss, Janney, Elstner Associates Inc., Northbrook, IL 60062, USA
authorships[3].author.id	https://openalex.org/A5081817597
authorships[3].author.orcid	https://orcid.org/0000-0002-7593-8509
authorships[3].author.display_name	Amir H. Alavi
authorships[3].countries	TW, US
authorships[3].affiliations[0].institution_ids	https://openalex.org/I170201317
authorships[3].affiliations[0].raw_affiliation_string	Department of Civil and Environmental Engineering, University of Pittsburgh, Pittsburgh, PA 15261, USA
authorships[3].affiliations[1].institution_ids	https://openalex.org/I143578492
authorships[3].affiliations[1].raw_affiliation_string	Department of Computer Science and Information Engineering, Asia University, Taichung, Taiwan 41354, China
authorships[3].institutions[0].id	https://openalex.org/I143578492
authorships[3].institutions[0].ror	https://ror.org/038a1tp19
authorships[3].institutions[0].type	education
authorships[3].institutions[0].lineage	https://openalex.org/I143578492
authorships[3].institutions[0].country_code	TW
authorships[3].institutions[0].display_name	Asia University
authorships[3].institutions[1].id	https://openalex.org/I170201317
authorships[3].institutions[1].ror	https://ror.org/01an3r305
authorships[3].institutions[1].type	education
authorships[3].institutions[1].lineage	https://openalex.org/I170201317
authorships[3].institutions[1].country_code	US
authorships[3].institutions[1].display_name	University of Pittsburgh
authorships[3].author_position	last
authorships[3].raw_author_name	Amir H. Alavi
authorships[3].is_corresponding	True
authorships[3].raw_affiliation_strings	Department of Civil and Environmental Engineering, University of Pittsburgh, Pittsburgh, PA 15261, USA, Department of Computer Science and Information Engineering, Asia University, Taichung, Taiwan 41354, China
has_content.pdf	False
has_content.grobid_xml	False
is_paratext	False
open_access.is_oa	True
open_access.oa_url	https://doi.org/10.1016/j.eng.2020.07.026
open_access.oa_status	gold
open_access.any_repository_has_fulltext	False
created_date	2025-10-10T00:00:00
display_name	Real-Time Detection of Cracks on Concrete Bridge Decks Using Deep Learning in the Frequency Domain
has_fulltext	False
is_retracted	False
updated_date	2025-11-06T03:46:38.306776
primary_topic.id	https://openalex.org/T11606
primary_topic.field.id	https://openalex.org/fields/22
primary_topic.field.display_name	Engineering
primary_topic.score	1.0
primary_topic.domain.id	https://openalex.org/domains/3
primary_topic.domain.display_name	Physical Sciences
primary_topic.subfield.id	https://openalex.org/subfields/2205
primary_topic.subfield.display_name	Civil and Structural Engineering
primary_topic.display_name	Infrastructure Maintenance and Monitoring
related_works	https://openalex.org/W2989490741, https://openalex.org/W3092506759, https://openalex.org/W2367545121, https://openalex.org/W4248881655, https://openalex.org/W2482165163, https://openalex.org/W3010890513, https://openalex.org/W120741642, https://openalex.org/W138569904, https://openalex.org/W2390914021, https://openalex.org/W2389417819
cited_by_count	130
counts_by_year[0].year	2025
counts_by_year[0].cited_by_count	30
counts_by_year[1].year	2024
counts_by_year[1].cited_by_count	33
counts_by_year[2].year	2023
counts_by_year[2].cited_by_count	34
counts_by_year[3].year	2022
counts_by_year[3].cited_by_count	25
counts_by_year[4].year	2021
counts_by_year[4].cited_by_count	8
locations_count	1
best_oa_location.id	doi:10.1016/j.eng.2020.07.026
best_oa_location.is_oa	True
best_oa_location.source.id	https://openalex.org/S4210192142
best_oa_location.source.issn	2095-8099, 2096-0026
best_oa_location.source.type	journal
best_oa_location.source.is_oa	True
best_oa_location.source.issn_l	2095-8099
best_oa_location.source.is_core	True
best_oa_location.source.is_in_doaj	True
best_oa_location.source.display_name	Engineering
best_oa_location.source.host_organization	https://openalex.org/P4310320990
best_oa_location.source.host_organization_name	Elsevier BV
best_oa_location.source.host_organization_lineage	https://openalex.org/P4310320990
best_oa_location.source.host_organization_lineage_names	Elsevier BV
best_oa_location.license	cc-by-nc-nd
best_oa_location.pdf_url
best_oa_location.version	publishedVersion
best_oa_location.raw_type	journal-article
best_oa_location.license_id	https://openalex.org/licenses/cc-by-nc-nd
best_oa_location.is_accepted	True
best_oa_location.is_published	True
best_oa_location.raw_source_name	Engineering
best_oa_location.landing_page_url	https://doi.org/10.1016/j.eng.2020.07.026
primary_location.id	doi:10.1016/j.eng.2020.07.026
primary_location.is_oa	True
primary_location.source.id	https://openalex.org/S4210192142
primary_location.source.issn	2095-8099, 2096-0026
primary_location.source.type	journal
primary_location.source.is_oa	True
primary_location.source.issn_l	2095-8099
primary_location.source.is_core	True
primary_location.source.is_in_doaj	True
primary_location.source.display_name	Engineering
primary_location.source.host_organization	https://openalex.org/P4310320990
primary_location.source.host_organization_name	Elsevier BV
primary_location.source.host_organization_lineage	https://openalex.org/P4310320990
primary_location.source.host_organization_lineage_names	Elsevier BV
primary_location.license	cc-by-nc-nd
primary_location.pdf_url
primary_location.version	publishedVersion
primary_location.raw_type	journal-article
primary_location.license_id	https://openalex.org/licenses/cc-by-nc-nd
primary_location.is_accepted	True
primary_location.is_published	True
primary_location.raw_source_name	Engineering
primary_location.landing_page_url	https://doi.org/10.1016/j.eng.2020.07.026
publication_date	2020-11-19
publication_year	2020
referenced_works	https://openalex.org/W2922073063, https://openalex.org/W2919946988, https://openalex.org/W2976474645, https://openalex.org/W2480267542, https://openalex.org/W2076387959, https://openalex.org/W6670128979, https://openalex.org/W1759600866, https://openalex.org/W2154805199, https://openalex.org/W2106238010, https://openalex.org/W2144801789, https://openalex.org/W1993097837, https://openalex.org/W2979549919, https://openalex.org/W2980472264, https://openalex.org/W2169303706, https://openalex.org/W130013534, https://openalex.org/W1596173341, https://openalex.org/W2325975990, https://openalex.org/W6681813608, https://openalex.org/W6684191040, https://openalex.org/W2756789966, https://openalex.org/W2890179326, https://openalex.org/W6757085564, https://openalex.org/W2983280015, https://openalex.org/W2919115771, https://openalex.org/W2990423348, https://openalex.org/W6609025380, https://openalex.org/W2598457882, https://openalex.org/W2810123099, https://openalex.org/W2168893862, https://openalex.org/W4244461127, https://openalex.org/W1523493493, https://openalex.org/W2076063813, https://openalex.org/W2064675550, https://openalex.org/W2121029939, https://openalex.org/W2805707465, https://openalex.org/W2889717020, https://openalex.org/W1689711448, https://openalex.org/W2758361465, https://openalex.org/W2610635404, https://openalex.org/W2770058012, https://openalex.org/W2605443677, https://openalex.org/W1600744878, https://openalex.org/W2904910227, https://openalex.org/W6625448046, https://openalex.org/W2125527601, https://openalex.org/W2100925004, https://openalex.org/W2113945798, https://openalex.org/W2271840356, https://openalex.org/W2145023731, https://openalex.org/W234388709, https://openalex.org/W2498076460, https://openalex.org/W2887124204, https://openalex.org/W571870154, https://openalex.org/W2163605009, https://openalex.org/W4300907038, https://openalex.org/W4229921563, https://openalex.org/W962245595, https://openalex.org/W2904906816
referenced_works_count	58
abstract_inverted_index.a	3, 64, 156
abstract_inverted_index.An	110
abstract_inverted_index.In	48
abstract_inverted_index.an	13
abstract_inverted_index.in	26, 133, 140
abstract_inverted_index.is	35, 69, 78, 98, 113
abstract_inverted_index.it	155
abstract_inverted_index.of	39, 41, 84, 94, 119, 142, 150
abstract_inverted_index.to	50, 80
abstract_inverted_index.The	31, 67, 92, 126, 147
abstract_inverted_index.and	20, 43, 101, 107, 144
abstract_inverted_index.are	56
abstract_inverted_index.for	8, 88, 104, 116, 123, 159
abstract_inverted_index.the	27, 52, 60, 73, 82, 85, 95, 120, 151
abstract_inverted_index.LSTM	77
abstract_inverted_index.This	0
abstract_inverted_index.deep	137
abstract_inverted_index.fast	148
abstract_inverted_index.into	59
abstract_inverted_index.long	21, 89
abstract_inverted_index.then	70
abstract_inverted_index.tool	158
abstract_inverted_index.used	79
abstract_inverted_index.with	135
abstract_inverted_index.crack	5, 161
abstract_inverted_index.data.	76, 91, 109
abstract_inverted_index.decks	11
abstract_inverted_index.first	57
abstract_inverted_index.image	28
abstract_inverted_index.makes	154
abstract_inverted_index.model	97, 122
abstract_inverted_index.order	49
abstract_inverted_index.paper	1
abstract_inverted_index.terms	141
abstract_inverted_index.time.	146
abstract_inverted_index.using	12, 37, 72
abstract_inverted_index.(LSTM)	24
abstract_inverted_index.98.9%,	100
abstract_inverted_index.bridge	10, 46
abstract_inverted_index.decks.	47
abstract_inverted_index.domain	62
abstract_inverted_index.during	63
abstract_inverted_index.future	117
abstract_inverted_index.images	40, 55
abstract_inverted_index.memory	23
abstract_inverted_index.method	25, 129
abstract_inverted_index.neural	17
abstract_inverted_index.phase.	66
abstract_inverted_index.99.05%,	99
abstract_inverted_index.99.25%,	102
abstract_inverted_index.cracked	42
abstract_inverted_index.domain.	30
abstract_inverted_index.further	114
abstract_inverted_index.images.	125
abstract_inverted_index.improve	51, 81
abstract_inverted_index.methods	139
abstract_inverted_index.network	18, 87
abstract_inverted_index.testing	108
abstract_inverted_index.trained	36, 121
abstract_inverted_index.(1D-CNN)	19
abstract_inverted_index.accuracy	93, 143
abstract_inverted_index.approach	7
abstract_inverted_index.concrete	9, 45
abstract_inverted_index.exhibits	130
abstract_inverted_index.existing	136
abstract_inverted_index.learning	138
abstract_inverted_index.presents	2
abstract_inverted_index.proposed	127
abstract_inverted_index.sequence	90
abstract_inverted_index.superior	131
abstract_inverted_index.training	53
abstract_inverted_index.algorithm	34, 68, 153
abstract_inverted_index.detection	6
abstract_inverted_index.developed	86, 96, 115
abstract_inverted_index.flattened	74
abstract_inverted_index.framework	112
abstract_inverted_index.frequency	29, 61, 75
abstract_inverted_index.promising	157
abstract_inverted_index.real-time	160
abstract_inverted_index.so-called	32
abstract_inverted_index.thousands	38
abstract_inverted_index.training,	105
abstract_inverted_index.calibrated	71
abstract_inverted_index.comparison	134
abstract_inverted_index.detection.	162
abstract_inverted_index.integrated	14
abstract_inverted_index.short-term	22
abstract_inverted_index.1D-CNN-LSTM	33, 128, 152
abstract_inverted_index.application	118
abstract_inverted_index.computation	145
abstract_inverted_index.efficiency,	54
abstract_inverted_index.large-scale	124
abstract_inverted_index.non-cracked	44
abstract_inverted_index.performance	83, 132
abstract_inverted_index.transformed	58
abstract_inverted_index.validation,	106
abstract_inverted_index.vision-based	4
abstract_inverted_index.convolutional	16
abstract_inverted_index.preprocessing	65
abstract_inverted_index.respectively,	103
abstract_inverted_index.implementation	111, 149
abstract_inverted_index.one-dimensional	15
cited_by_percentile_year.max	100
cited_by_percentile_year.min	98
corresponding_author_ids	https://openalex.org/A5081817597
countries_distinct_count	2
institutions_distinct_count	4
corresponding_institution_ids	https://openalex.org/I143578492, https://openalex.org/I170201317
sustainable_development_goals[0].id	https://metadata.un.org/sdg/9
sustainable_development_goals[0].score	0.4399999976158142
sustainable_development_goals[0].display_name	Industry, innovation and infrastructure
citation_normalized_percentile.value	0.98943919
citation_normalized_percentile.is_in_top_1_percent	True
citation_normalized_percentile.is_in_top_10_percent	True