Publication Information

{'id': 'https://openalex.org/W2130982917', 'doi': 'https://doi.org/10.1109/tnn.2003.813829', 'title': 'Independent component analysis of gabor features for face recognition', 'display_name': 'Independent component analysis of gabor features for face recognition', 'publication_year': 2003, 'publication_date': '2003-07-01', 'ids': {'openalex': 'https://openalex.org/W2130982917', 'doi': 'https://doi.org/10.1109/tnn.2003.813829', 'mag': '2130982917', 'pmid': 'https://pubmed.ncbi.nlm.nih.gov/18238070'}, 'language': 'en', 'primary_location': {'is_oa': False, 'landing_page_url': 'https://doi.org/10.1109/tnn.2003.813829', 'pdf_url': None, 'source': {'id': 'https://openalex.org/S42080949', 'display_name': 'IEEE Transactions on Neural Networks', 'issn_l': '1045-9227', 'issn': ['1045-9227', '1941-0093'], 'is_oa': False, 'is_in_doaj': False, 'is_core': True, 'host_organization': 'https://openalex.org/P4310319808', 'host_organization_name': 'Institute of Electrical and Electronics Engineers', 'host_organization_lineage': ['https://openalex.org/P4310319808'], 'host_organization_lineage_names': ['Institute of Electrical and Electronics Engineers'], 'type': 'journal'}, 'license': None, 'license_id': None, 'version': None, 'is_accepted': False, 'is_published': False}, 'type': 'article', 'type_crossref': 'journal-article', 'indexed_in': ['crossref', 'pubmed'], '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/A5108489454', 'display_name': 'Chengjun Liu', 'orcid': None}, 'institutions': [{'id': 'https://openalex.org/I118118575', 'display_name': 'New Jersey Institute of Technology', 'ror': 'https://ror.org/05e74xb87', 'country_code': 'US', 'type': 'education', 'lineage': ['https://openalex.org/I118118575']}], 'countries': ['US'], 'is_corresponding': False, 'raw_author_name': 'None Chengjun Liu', 'raw_affiliation_strings': ['Department of Computer Science; New Jersey Institute of Technology; Newark NJ USA'], 'affiliations': [{'raw_affiliation_string': 'Department of Computer Science; New Jersey Institute of Technology; Newark NJ USA', 'institution_ids': ['https://openalex.org/I118118575']}]}, {'author_position': 'last', 'author': {'id': 'https://openalex.org/A5058156010', 'display_name': 'Harry Wechsler', 'orcid': 'https://orcid.org/0000-0002-5454-8819'}, 'institutions': [{'id': 'https://openalex.org/I162714631', 'display_name': 'George Mason University', 'ror': 'https://ror.org/02jqj7156', 'country_code': 'US', 'type': 'education', 'lineage': ['https://openalex.org/I162714631']}], 'countries': ['US'], 'is_corresponding': False, 'raw_author_name': 'H. Wechsler', 'raw_affiliation_strings': ['Department of Computer Science, George Mason University , Fairfax, VA, USA.'], 'affiliations': [{'raw_affiliation_string': 'Department of Computer Science, George Mason University , Fairfax, VA, USA.', 'institution_ids': ['https://openalex.org/I162714631']}]}], 'institution_assertions': [], 'countries_distinct_count': 1, 'institutions_distinct_count': 2, 'corresponding_author_ids': [], 'corresponding_institution_ids': [], 'apc_list': None, 'apc_paid': None, 'fwci': 18.723, 'has_fulltext': True, 'fulltext_origin': 'ngrams', 'cited_by_count': 470, 'citation_normalized_percentile': {'value': 0.980437, 'is_in_top_1_percent': False, 'is_in_top_10_percent': True}, 'cited_by_percentile_year': {'min': 99, 'max': 100}, 'biblio': {'volume': '14', 'issue': '4', 'first_page': '919', 'last_page': '928'}, 'is_retracted': False, 'is_paratext': False, 'primary_topic': {'id': 'https://openalex.org/T11447', 'display_name': 'Blind Source Separation Techniques', 'score': 0.9995, 'subfield': {'id': 'https://openalex.org/subfields/1711', 'display_name': 'Signal Processing'}, 'field': {'id': 'https://openalex.org/fields/17', 'display_name': 'Computer Science'}, 'domain': {'id': 'https://openalex.org/domains/3', 'display_name': 'Physical Sciences'}}, 'topics': [{'id': 'https://openalex.org/T11447', 'display_name': 'Blind Source Separation Techniques', 'score': 0.9995, 'subfield': {'id': 'https://openalex.org/subfields/1711', 'display_name': 'Signal Processing'}, '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/T10057', 'display_name': 'Face and Expression Recognition', 'score': 0.9981, '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/T10689', 'display_name': 'Remote-Sensing Image Classification', 'score': 0.9924, 'subfield': {'id': 'https://openalex.org/subfields/2214', 'display_name': 'Media Technology'}, 'field': {'id': 'https://openalex.org/fields/22', 'display_name': 'Engineering'}, 'domain': {'id': 'https://openalex.org/domains/3', 'display_name': 'Physical Sciences'}}], 'keywords': [{'id': 'https://openalex.org/keywords/gabor-wavelet', 'display_name': 'Gabor wavelet', 'score': 0.80494165}, {'id': 'https://openalex.org/keywords/feature-vector', 'display_name': 'Feature vector', 'score': 0.41674843}], 'concepts': [{'id': 'https://openalex.org/C153180895', 'wikidata': 'https://www.wikidata.org/wiki/Q7148389', 'display_name': 'Pattern recognition (psychology)', 'level': 2, 'score': 0.85227895}, {'id': 'https://openalex.org/C136902061', 'wikidata': 'https://www.wikidata.org/wiki/Q16981559', 'display_name': 'Gabor wavelet', 'level': 5, 'score': 0.80494165}, {'id': 'https://openalex.org/C154945302', 'wikidata': 'https://www.wikidata.org/wiki/Q11660', 'display_name': 'Artificial intelligence', 'level': 1, 'score': 0.7992127}, {'id': 'https://openalex.org/C41008148', 'wikidata': 'https://www.wikidata.org/wiki/Q21198', 'display_name': 'Computer science', 'level': 0, 'score': 0.64946985}, {'id': 'https://openalex.org/C31510193', 'wikidata': 'https://www.wikidata.org/wiki/Q1192553', 'display_name': 'Facial recognition system', 'level': 3, 'score': 0.64685005}, {'id': 'https://openalex.org/C51432778', 'wikidata': 'https://www.wikidata.org/wiki/Q1259145', 'display_name': 'Independent component analysis', 'level': 2, 'score': 0.588501}, {'id': 'https://openalex.org/C27438332', 'wikidata': 'https://www.wikidata.org/wiki/Q2873', 'display_name': 'Principal component analysis', 'level': 2, 'score': 0.5062715}, {'id': 'https://openalex.org/C52622490', 'wikidata': 'https://www.wikidata.org/wiki/Q1026626', 'display_name': 'Feature extraction', 'level': 2, 'score': 0.4959019}, {'id': 'https://openalex.org/C2779304628', 'wikidata': 'https://www.wikidata.org/wiki/Q3503480', 'display_name': 'Face (sociological concept)', 'level': 2, 'score': 0.4660887}, {'id': 'https://openalex.org/C83665646', 'wikidata': 'https://www.wikidata.org/wiki/Q42139305', 'display_name': 'Feature vector', 'level': 2, 'score': 0.41674843}, {'id': 'https://openalex.org/C31972630', 'wikidata': 'https://www.wikidata.org/wiki/Q844240', 'display_name': 'Computer vision', 'level': 1, 'score': 0.39239776}, {'id': 'https://openalex.org/C196216189', 'wikidata': 'https://www.wikidata.org/wiki/Q2867', 'display_name': 'Wavelet transform', 'level': 3, 'score': 0.31695533}, {'id': 'https://openalex.org/C47432892', 'wikidata': 'https://www.wikidata.org/wiki/Q831390', 'display_name': 'Wavelet', 'level': 2, 'score': 0.26859486}, {'id': 'https://openalex.org/C46286280', 'wikidata': 'https://www.wikidata.org/wiki/Q2414958', 'display_name': 'Discrete wavelet transform', 'level': 4, 'score': 0.2657351}, {'id': 'https://openalex.org/C36289849', 'wikidata': 'https://www.wikidata.org/wiki/Q34749', 'display_name': 'Social science', 'level': 1, 'score': 0.0}, {'id': 'https://openalex.org/C144024400', 'wikidata': 'https://www.wikidata.org/wiki/Q21201', 'display_name': 'Sociology', 'level': 0, 'score': 0.0}], 'mesh': [], 'locations_count': 2, 'locations': [{'is_oa': False, 'landing_page_url': 'https://doi.org/10.1109/tnn.2003.813829', 'pdf_url': None, 'source': {'id': 'https://openalex.org/S42080949', 'display_name': 'IEEE Transactions on Neural Networks', 'issn_l': '1045-9227', 'issn': ['1045-9227', '1941-0093'], 'is_oa': False, 'is_in_doaj': False, 'is_core': True, 'host_organization': 'https://openalex.org/P4310319808', 'host_organization_name': 'Institute of Electrical and Electronics Engineers', 'host_organization_lineage': ['https://openalex.org/P4310319808'], 'host_organization_lineage_names': ['Institute of Electrical and Electronics Engineers'], 'type': 'journal'}, 'license': None, 'license_id': None, 'version': None, 'is_accepted': False, 'is_published': False}, {'is_oa': False, 'landing_page_url': 'https://pubmed.ncbi.nlm.nih.gov/18238070', 'pdf_url': None, 'source': {'id': 'https://openalex.org/S4306525036', 'display_name': 'PubMed', 'issn_l': None, 'issn': None, 'is_oa': False, 'is_in_doaj': False, 'is_core': False, 'host_organization': 'https://openalex.org/I1299303238', 'host_organization_name': 'National Institutes of Health', 'host_organization_lineage': ['https://openalex.org/I1299303238'], 'host_organization_lineage_names': ['National Institutes of Health'], 'type': 'repository'}, 'license': None, 'license_id': None, 'version': None, 'is_accepted': False, 'is_published': False}], 'best_oa_location': None, 'sustainable_development_goals': [{'display_name': 'Reduced inequalities', 'id': 'https://metadata.un.org/sdg/10', 'score': 0.51}, {'display_name': 'Peace, justice, and strong institutions', 'id': 'https://metadata.un.org/sdg/16', 'score': 0.41}], 'grants': [], 'datasets': [], 'versions': [], 'referenced_works_count': 56, 'referenced_works': ['https://openalex.org/W1555711139', 'https://openalex.org/W1586420997', 'https://openalex.org/W1759219755', 'https://openalex.org/W1914401667', 'https://openalex.org/W1964415410', 'https://openalex.org/W1997011019', 'https://openalex.org/W2014102379', 'https://openalex.org/W2019487368', 'https://openalex.org/W2019502123', 'https://openalex.org/W2021012145', 'https://openalex.org/W2035782554', 'https://openalex.org/W2040179990', 'https://openalex.org/W2072652250', 'https://openalex.org/W2078916996', 'https://openalex.org/W2085927826', 'https://openalex.org/W2092537568', 'https://openalex.org/W2095757522', 'https://openalex.org/W2096044434', 'https://openalex.org/W2096789154', 'https://openalex.org/W2096813265', 'https://openalex.org/W2097836861', 'https://openalex.org/W2099312605', 'https://openalex.org/W2099741732', 'https://openalex.org/W2100281586', 'https://openalex.org/W2103384342', 'https://openalex.org/W2106884367', 'https://openalex.org/W2109792354', 'https://openalex.org/W2115304588', 'https://openalex.org/W2115689562', 'https://openalex.org/W2115943089', 'https://openalex.org/W2120954940', 'https://openalex.org/W2127530969', 'https://openalex.org/W2128716185', 'https://openalex.org/W2133180260', 'https://openalex.org/W2135192052', 'https://openalex.org/W2135463994', 'https://openalex.org/W2136405083', 'https://openalex.org/W2138451337', 'https://openalex.org/W2138584058', 'https://openalex.org/W2144354855', 'https://openalex.org/W2145889472', 'https://openalex.org/W2146474141', 'https://openalex.org/W2152473410', 'https://openalex.org/W2155511848', 'https://openalex.org/W2156372879', 'https://openalex.org/W2156909104', 'https://openalex.org/W2158247472', 'https://openalex.org/W2159686933', 'https://openalex.org/W2163280874', 'https://openalex.org/W2163965432', 'https://openalex.org/W2167034998', 'https://openalex.org/W2180187800', 'https://openalex.org/W2217896605', 'https://openalex.org/W2485341146', 'https://openalex.org/W4210668077', 'https://openalex.org/W622311078'], 'related_works': ['https://openalex.org/W55679925', 'https://openalex.org/W4252230435', 'https://openalex.org/W3080404860', 'https://openalex.org/W2356622597', 'https://openalex.org/W2182042810', 'https://openalex.org/W2164017354', 'https://openalex.org/W2141351178', 'https://openalex.org/W2121429698', 'https://openalex.org/W2046761971', 'https://openalex.org/W1680053903'], 'abstract_inverted_index': {'We': [0], 'present': [1], 'an': [2, 39], 'independent': [3, 26, 92, 98, 175, 179], 'Gabor': [4, 27, 61, 69, 93, 107, 123, 135], 'features': [5, 28, 94, 108, 156, 176, 180, 236], '(IGFs)': [6], 'method': [7, 19, 47, 57, 115, 226], 'and': [8, 34, 88, 125, 146, 173, 188, 201, 213, 241], 'its': [9], 'application': [10, 111], 'to': [11], 'face': [12, 73, 137, 162, 193, 230], 'recognition.': [13, 163], 'The': [14, 102, 118], 'novelty': [15], 'of': [16, 25, 38, 67, 72, 79, 84, 105, 112, 142, 218], 'the': [17, 23, 30, 36, 49, 55, 77, 80, 91, 97, 110, 113, 122, 126, 131, 134, 165, 196, 202, 206, 216, 219, 224, 238, 245], 'IGF': [18, 40, 56, 220, 225], 'comes': [20], 'from': [21, 64], '1)': [22], 'derivation': [24], 'in': [29, 48, 209], 'feature': [31, 62], 'extraction': [32], 'stage': [33], '2)': [35], 'development': [37], 'features-based': [41], 'probabilistic': [42], 'reasoning': [43], 'model': [44], '(PRM)': [45], 'classification': [46], 'pattern': [50, 186], 'recognition': [51, 194, 231], 'stage.': [52], 'In': [53, 222], 'particular,': [54, 223], 'first': [58], 'derives': [59], 'a': [60, 65], 'vector': [63, 81], 'set': [66], 'downsampled': [68], 'wavelet': [70], 'representations': [71], 'images,': [74], 'then': [75], 'reduces': [76], 'dimensionality': [78], 'by': [82], 'means': [83], 'principal': [85], 'component': [86, 99], 'analysis,': [87], 'finally': [89], 'defines': [90], 'based': [95], 'on': [96, 192], 'analysis': [100], '(ICA).': [101], 'independence': [103], 'property': [104], 'these': [106], 'facilitates': [109], 'PRM': [114], 'for': [116, 161, 184, 237, 244], 'classification.': [117], 'rationale': [119], 'behind': [120], 'integrating': [121], 'wavelets': [124], 'ICA': [127, 168], 'is': [128], 'twofold.': [129], 'On': [130, 164], 'one': [132], 'hand,': [133, 167], 'transformed': [136], 'images': [138, 150, 207], 'exhibit': [139], 'strong': [140], 'characteristics': [141], 'spatial': [143], 'locality,': [144], 'scale,': [145, 214], 'orientation': [147], 'selectivity.': [148], 'These': [149, 178], 'can,': [151], 'thus,': [152], 'produce': [153], 'salient': [154], 'local': [155], 'that': [157], 'are': [158, 181], 'most': [159, 182], 'suitable': [160], 'other': [166], 'would': [169], 'further': [170], 'reduce': [171], 'redundancy': [172], 'represent': [174], 'explicitly.': [177], 'useful': [183], 'subsequent': [185], 'discrimination': [187], 'associative': [189], 'recall.': [190], 'Experiments': [191], 'using': [195, 234, 248], 'FacE': [197], 'REcognition': [198], 'Technology': [199], '(FERET)': [200], 'ORL': [203, 246], 'datasets,': [204], 'where': [205], 'vary': [208], 'illumination,': [210], 'expression,': [211], 'pose,': [212], 'show': [215], 'feasibility': [217], 'method.': [221], 'achieves': [227], '98.5%': [228], 'correct': [229], 'accuracy': [232, 243], 'when': [233], '180': [235], 'FERET': [239], 'dataset,': [240], '100%': [242], 'dataset': [247], '88': [249], 'features.': [250]}, 'cited_by_api_url': 'https://api.openalex.org/works?filter=cites:W2130982917', 'counts_by_year': [{'year': 2024, 'cited_by_count': 1}, {'year': 2023, 'cited_by_count': 7}, {'year': 2022, 'cited_by_count': 7}, {'year': 2021, 'cited_by_count': 4}, {'year': 2020, 'cited_by_count': 14}, {'year': 2019, 'cited_by_count': 13}, {'year': 2018, 'cited_by_count': 12}, {'year': 2017, 'cited_by_count': 27}, {'year': 2016, 'cited_by_count': 19}, {'year': 2015, 'cited_by_count': 22}, {'year': 2014, 'cited_by_count': 34}, {'year': 2013, 'cited_by_count': 28}, {'year': 2012, 'cited_by_count': 36}], 'updated_date': '2024-12-13T17:36:04.498832', 'created_date': '2016-06-24'}