Publication Information

{'id': 'https://openalex.org/W3176347655', 'doi': 'https://doi.org/10.1145/3457682.3457728', 'title': 'An Effective Method of Wood Crack Trace and Quantity Detection Based on Digital Image Processing Technology', 'display_name': 'An Effective Method of Wood Crack Trace and Quantity Detection Based on Digital Image Processing Technology', 'publication_year': 2021, 'publication_date': '2021-02-26', 'ids': {'openalex': 'https://openalex.org/W3176347655', 'doi': 'https://doi.org/10.1145/3457682.3457728', 'mag': '3176347655'}, 'language': 'en', 'primary_location': {'is_oa': False, 'landing_page_url': 'https://doi.org/10.1145/3457682.3457728', 'pdf_url': None, 'source': None, 'license': None, 'license_id': None, 'version': None, 'is_accepted': False, 'is_published': False}, 'type': 'article', 'type_crossref': 'proceedings-article', 'indexed_in': ['crossref'], 'open_access': {'is_oa': False, 'oa_status': 'closed', 'oa_url': None, 'any_repository_has_fulltext': False}, 'authorships': [{'author_position': 'first', 'author': {'id': 'https://openalex.org/A5036842788', 'display_name': 'Xinning Cao', 'orcid': None}, 'institutions': [{'id': 'https://openalex.org/I154099455', 'display_name': 'Shandong University', 'ror': 'https://ror.org/0207yh398', 'country_code': 'CN', 'type': 'education', 'lineage': ['https://openalex.org/I154099455']}], 'countries': ['CN'], 'is_corresponding': False, 'raw_author_name': 'Xinning Cao', 'raw_affiliation_strings': ['Shandong University, China'], 'affiliations': [{'raw_affiliation_string': 'Shandong University, China', 'institution_ids': ['https://openalex.org/I154099455']}]}, {'author_position': 'last', 'author': {'id': 'https://openalex.org/A5100635452', 'display_name': 'Guangming Li', 'orcid': 'https://orcid.org/0000-0002-6928-051X'}, 'institutions': [{'id': 'https://openalex.org/I154099455', 'display_name': 'Shandong University', 'ror': 'https://ror.org/0207yh398', 'country_code': 'CN', 'type': 'education', 'lineage': ['https://openalex.org/I154099455']}], 'countries': ['CN'], 'is_corresponding': False, 'raw_author_name': 'Guangming Li', 'raw_affiliation_strings': ['Shandong University, China'], 'affiliations': [{'raw_affiliation_string': 'Shandong University, China', 'institution_ids': ['https://openalex.org/I154099455']}]}], 'institution_assertions': [], 'countries_distinct_count': 1, 'institutions_distinct_count': 1, 'corresponding_author_ids': [], 'corresponding_institution_ids': [], 'apc_list': None, 'apc_paid': None, 'fwci': 3.33, 'has_fulltext': False, 'cited_by_count': 8, 'citation_normalized_percentile': {'value': 0.904932, 'is_in_top_1_percent': False, 'is_in_top_10_percent': True}, 'cited_by_percentile_year': {'min': 85, 'max': 87}, 'biblio': {'volume': None, 'issue': None, 'first_page': None, 'last_page': None}, 'is_retracted': False, 'is_paratext': False, 'primary_topic': {'id': 'https://openalex.org/T12111', 'display_name': 'Fabric Defect Detection in Industrial Applications', 'score': 0.9998, 'subfield': {'id': 'https://openalex.org/subfields/2209', 'display_name': 'Industrial and Manufacturing Engineering'}, 'field': {'id': 'https://openalex.org/fields/22', 'display_name': 'Engineering'}, 'domain': {'id': 'https://openalex.org/domains/3', 'display_name': 'Physical Sciences'}}, 'topics': [{'id': 'https://openalex.org/T12111', 'display_name': 'Fabric Defect Detection in Industrial Applications', 'score': 0.9998, 'subfield': {'id': 'https://openalex.org/subfields/2209', 'display_name': 'Industrial and Manufacturing Engineering'}, 'field': {'id': 'https://openalex.org/fields/22', 'display_name': 'Engineering'}, 'domain': {'id': 'https://openalex.org/domains/3', 'display_name': 'Physical Sciences'}}, {'id': 'https://openalex.org/T12549', 'display_name': 'Robust Line and Curve Detection using Hough Transform', 'score': 0.9942, 'subfield': {'id': 'https://openalex.org/subfields/1707', 'display_name': 'Computer Vision and Pattern Recognition'}, 'field': {'id': 'https://openalex.org/fields/17', 'display_name': 'Computer Science'}, 'domain': {'id': 'https://openalex.org/domains/3', 'display_name': 'Physical Sciences'}}, {'id': 'https://openalex.org/T13568', 'display_name': 'Chemical Constituents and Production of Agarwood', 'score': 0.992, 'subfield': {'id': 'https://openalex.org/subfields/1605', 'display_name': 'Organic Chemistry'}, 'field': {'id': 'https://openalex.org/fields/16', 'display_name': 'Chemistry'}, 'domain': {'id': 'https://openalex.org/domains/3', 'display_name': 'Physical Sciences'}}], 'keywords': [{'id': 'https://openalex.org/keywords/wood-identification', 'display_name': 'Wood Identification', 'score': 0.625859}, {'id': 'https://openalex.org/keywords/edge-detection', 'display_name': 'Edge Detection', 'score': 0.576638}, {'id': 'https://openalex.org/keywords/fabric-defect-detection', 'display_name': 'Fabric Defect Detection', 'score': 0.566409}, {'id': 'https://openalex.org/keywords/line-detection', 'display_name': 'Line Detection', 'score': 0.565054}, {'id': 'https://openalex.org/keywords/real-time-detection', 'display_name': 'Real-Time Detection', 'score': 0.549903}], 'concepts': [{'id': 'https://openalex.org/C193828747', 'wikidata': 'https://www.wikidata.org/wiki/Q864118', 'display_name': 'Binary image', 'level': 4, 'score': 0.68524104}, {'id': 'https://openalex.org/C104317675', 'wikidata': 'https://www.wikidata.org/wiki/Q1070689', 'display_name': 'Digital image processing', 'level': 4, 'score': 0.65404564}, {'id': 'https://openalex.org/C9417928', 'wikidata': 'https://www.wikidata.org/wiki/Q1070689', 'display_name': 'Image processing', 'level': 3, 'score': 0.6446313}, {'id': 'https://openalex.org/C41008148', 'wikidata': 'https://www.wikidata.org/wiki/Q21198', 'display_name': 'Computer science', 'level': 0, 'score': 0.5350377}, {'id': 'https://openalex.org/C2780365114', 'wikidata': 'https://www.wikidata.org/wiki/Q169478', 'display_name': 'MATLAB', 'level': 2, 'score': 0.5144708}, {'id': 'https://openalex.org/C42781572', 'wikidata': 'https://www.wikidata.org/wiki/Q1250322', 'display_name': 'Digital image', 'level': 4, 'score': 0.51316553}, {'id': 'https://openalex.org/C124504099', 'wikidata': 'https://www.wikidata.org/wiki/Q56933', 'display_name': 'Image segmentation', 'level': 3, 'score': 0.49430537}, {'id': 'https://openalex.org/C31972630', 'wikidata': 'https://www.wikidata.org/wiki/Q844240', 'display_name': 'Computer vision', 'level': 1, 'score': 0.48165667}, {'id': 'https://openalex.org/C154945302', 'wikidata': 'https://www.wikidata.org/wiki/Q11660', 'display_name': 'Artificial intelligence', 'level': 1, 'score': 0.45242393}, {'id': 'https://openalex.org/C89600930', 'wikidata': 'https://www.wikidata.org/wiki/Q1423946', 'display_name': 'Segmentation', 'level': 2, 'score': 0.44905004}, {'id': 'https://openalex.org/C115961682', 'wikidata': 'https://www.wikidata.org/wiki/Q860623', 'display_name': 'Image (mathematics)', 'level': 2, 'score': 0.41541082}, {'id': 'https://openalex.org/C111919701', 'wikidata': 'https://www.wikidata.org/wiki/Q9135', 'display_name': 'Operating system', 'level': 1, 'score': 0.0}], 'mesh': [], 'locations_count': 1, 'locations': [{'is_oa': False, 'landing_page_url': 'https://doi.org/10.1145/3457682.3457728', 'pdf_url': None, 'source': None, 'license': None, 'license_id': None, 'version': None, 'is_accepted': False, 'is_published': False}], 'best_oa_location': None, 'sustainable_development_goals': [{'score': 0.6, 'display_name': 'Reduced inequalities', 'id': 'https://metadata.un.org/sdg/10'}], 'grants': [], 'datasets': [], 'versions': [], 'referenced_works_count': 2, 'referenced_works': ['https://openalex.org/W2053384090', 'https://openalex.org/W2927165698'], 'related_works': ['https://openalex.org/W3186605777', 'https://openalex.org/W3109925116', 'https://openalex.org/W3107295340', 'https://openalex.org/W3036827782', 'https://openalex.org/W2979230453', 'https://openalex.org/W2390627398', 'https://openalex.org/W2364342979', 'https://openalex.org/W2356087891', 'https://openalex.org/W2186450712', 'https://openalex.org/W2118514085'], 'abstract_inverted_index': {'With': [0], 'the': [1, 23, 42, 69, 75, 86, 96, 105, 113, 121, 125, 136, 147], 'rapid': [2], 'development': [3], 'of': [4, 28, 62, 71, 77, 82, 99, 104, 108, 115, 120, 146, 154], 'digital': [5, 24], 'image': [6, 25, 88, 127], 'processing': [7, 26], 'technology,': [8], 'wood': [9, 32, 38], 'quality': [10], 'detection': [11, 73], 'technology': [12, 27], 'has': [13], 'become': [14], 'more': [15, 18], 'convenient': [16], 'and': [17, 49, 79, 101, 112, 117, 142, 157], 'accurate.': [19], 'This': [20], 'paper': [21, 66], 'uses': [22], 'MATLAB': [29], 'to': [30, 132], 'detect': [31], 'cross-section': [33], 'cracks.': [34], 'However,': [35], 'in': [36, 124, 159], 'actual': [37], 'crack': [39, 47, 72, 126], 'detection,': [40], 'because': [41], 'gray': [43], 'level': [44], 'contrast': [45], 'between': [46], 'target': [48], 'background': [50], 'is': [51, 89, 110, 128, 149], 'not': [52], 'obvious,': [53], 'some': [54], 'small': [55], 'cracks': [56, 109, 138, 153], 'cannot': [57], 'be': [58], 'identified.': [59], 'In': [60], 'view': [61], 'this': [63, 65], 'phenomenon,': [64], 'puts': [67], 'forward': [68], 'method': [70, 148], 'by': [74, 91, 151], 'ratio': [76, 98, 114], 'long': [78, 100, 116], 'short': [80, 102, 118], 'axis': [81, 103, 119], 'connected': [83, 106, 122], 'domain.': [84], 'Firstly,': [85], 'binary': [87], 'obtained': [90], 'double': [92], 'threshold': [93], 'segmentation.': [94], 'Then,': [95], 'minimum': [97], 'domain': [107, 123], 'set,': [111], 'discriminated': [129], 'from': [130], 'it': [131], 'extract': [133], 'cracks;': [134], 'finally,': [135], 'extracted': [137], 'are': [139], 'marked,': [140], 'counted': [141], 'measured.': [143], 'The': [144], 'feasibility': [145], 'verified': [150], 'detecting': [152], 'different': [155], 'types': [156], 'degrees': [158], 'various': [160], 'experiments.': [161]}, 'cited_by_api_url': 'https://api.openalex.org/works?filter=cites:W3176347655', 'counts_by_year': [{'year': 2024, 'cited_by_count': 3}, {'year': 2023, 'cited_by_count': 4}, {'year': 2022, 'cited_by_count': 1}], 'updated_date': '2024-09-26T10:23:55.010132', 'created_date': '2021-07-05'}