Get quick answers to your questions about the article from our AI researcher chatbot
{'id': 'https://openalex.org/W2792114281', 'doi': 'https://doi.org/10.1080/01431161.2018.1452074', 'title': 'Multi spectral image fusion by deep convolutional neural network and new spectral loss function', 'display_name': 'Multi spectral image fusion by deep convolutional neural network and new spectral loss function', 'publication_year': 2018, 'publication_date': '2018-03-23', 'ids': {'openalex': 'https://openalex.org/W2792114281', 'doi': 'https://doi.org/10.1080/01431161.2018.1452074', 'mag': '2792114281'}, 'language': 'en', 'primary_location': {'is_oa': False, 'landing_page_url': 'https://doi.org/10.1080/01431161.2018.1452074', 'pdf_url': None, 'source': {'id': 'https://openalex.org/S117411352', 'display_name': 'International Journal of Remote Sensing', 'issn_l': '0143-1161', 'issn': ['0143-1161', '1366-5901'], 'is_oa': False, 'is_in_doaj': False, 'is_core': True, 'host_organization': 'https://openalex.org/P4310320547', 'host_organization_name': 'Taylor & Francis', 'host_organization_lineage': ['https://openalex.org/P4310320547'], 'host_organization_lineage_names': ['Taylor & Francis'], 'type': 'journal'}, 'license': None, 'license_id': None, 'version': None, 'is_accepted': False, 'is_published': False}, 'type': 'article', 'type_crossref': 'journal-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/A5037435408', 'display_name': 'Sajjad Eghbalian', 'orcid': None}, 'institutions': [{'id': 'https://openalex.org/I1516879', 'display_name': 'Tarbiat Modares University', 'ror': 'https://ror.org/03mwgfy56', 'country_code': 'IR', 'type': 'education', 'lineage': ['https://openalex.org/I1516879']}], 'countries': ['IR'], 'is_corresponding': False, 'raw_author_name': 'Sajjad Eghbalian', 'raw_affiliation_strings': ['Image processing and Information Analysis Lab, Faculty of Electrical and Computer Engineering, Tarbiat Modares University, Tehran, Iran'], 'affiliations': [{'raw_affiliation_string': 'Image processing and Information Analysis Lab, Faculty of Electrical and Computer Engineering, Tarbiat Modares University, Tehran, Iran', 'institution_ids': ['https://openalex.org/I1516879']}]}, {'author_position': 'last', 'author': {'id': 'https://openalex.org/A5040092306', 'display_name': 'Hassan Ghassemian', 'orcid': 'https://orcid.org/0000-0002-2303-1753'}, 'institutions': [{'id': 'https://openalex.org/I1516879', 'display_name': 'Tarbiat Modares University', 'ror': 'https://ror.org/03mwgfy56', 'country_code': 'IR', 'type': 'education', 'lineage': ['https://openalex.org/I1516879']}], 'countries': ['IR'], 'is_corresponding': True, 'raw_author_name': 'Hassan Ghassemian', 'raw_affiliation_strings': ['Image processing and Information Analysis Lab, Faculty of Electrical and Computer Engineering, Tarbiat Modares University, Tehran, Iran'], 'affiliations': [{'raw_affiliation_string': 'Image processing and Information Analysis Lab, Faculty of Electrical and Computer Engineering, Tarbiat Modares University, Tehran, Iran', 'institution_ids': ['https://openalex.org/I1516879']}]}], 'institution_assertions': [], 'countries_distinct_count': 1, 'institutions_distinct_count': 1, 'corresponding_author_ids': ['https://openalex.org/A5040092306'], 'corresponding_institution_ids': ['https://openalex.org/I1516879'], 'apc_list': None, 'apc_paid': None, 'fwci': 4.246, 'has_fulltext': True, 'fulltext_origin': 'ngrams', 'cited_by_count': 35, 'citation_normalized_percentile': {'value': 0.999839, 'is_in_top_1_percent': True, 'is_in_top_10_percent': True}, 'cited_by_percentile_year': {'min': 94, 'max': 95}, 'biblio': {'volume': '39', 'issue': '12', 'first_page': '3983', 'last_page': '4002'}, 'is_retracted': False, 'is_paratext': False, 'primary_topic': {'id': 'https://openalex.org/T11659', 'display_name': 'Advanced Image Fusion Techniques', 'score': 1.0, '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'}}, 'topics': [{'id': 'https://openalex.org/T11659', 'display_name': 'Advanced Image Fusion Techniques', 'score': 1.0, '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'}}, {'id': 'https://openalex.org/T11019', 'display_name': 'Image Enhancement Techniques', 'score': 0.9973, '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': 0.9967, '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/panchromatic-film', 'display_name': 'Panchromatic film', 'score': 0.8932073}, {'id': 'https://openalex.org/keywords/convolution', 'display_name': 'Convolution (computer science)', 'score': 0.5260563}, {'id': 'https://openalex.org/keywords/distortion', 'display_name': 'Distortion (music)', 'score': 0.4513905}], 'concepts': [{'id': 'https://openalex.org/C107445234', 'wikidata': 'https://www.wikidata.org/wiki/Q280995', 'display_name': 'Panchromatic film', 'level': 3, 'score': 0.8932073}, {'id': 'https://openalex.org/C41008148', 'wikidata': 'https://www.wikidata.org/wiki/Q21198', 'display_name': 'Computer science', 'level': 0, 'score': 0.7372134}, {'id': 'https://openalex.org/C154945302', 'wikidata': 'https://www.wikidata.org/wiki/Q11660', 'display_name': 'Artificial intelligence', 'level': 1, 'score': 0.674636}, {'id': 'https://openalex.org/C173163844', 'wikidata': 'https://www.wikidata.org/wiki/Q1761440', 'display_name': 'Multispectral image', 'level': 2, 'score': 0.6379692}, {'id': 'https://openalex.org/C205372480', 'wikidata': 'https://www.wikidata.org/wiki/Q210521', 'display_name': 'Image resolution', 'level': 2, 'score': 0.62865365}, {'id': 'https://openalex.org/C81363708', 'wikidata': 'https://www.wikidata.org/wiki/Q17084460', 'display_name': 'Convolutional neural network', 'level': 2, 'score': 0.5888965}, {'id': 'https://openalex.org/C45347329', 'wikidata': 'https://www.wikidata.org/wiki/Q5166604', 'display_name': 'Convolution (computer science)', 'level': 3, 'score': 0.5260563}, {'id': 'https://openalex.org/C159620131', 'wikidata': 'https://www.wikidata.org/wiki/Q1938983', 'display_name': 'Spatial analysis', 'level': 2, 'score': 0.51732755}, {'id': 'https://openalex.org/C153180895', 'wikidata': 'https://www.wikidata.org/wiki/Q7148389', 'display_name': 'Pattern recognition (psychology)', 'level': 2, 'score': 0.5131}, {'id': 'https://openalex.org/C31972630', 'wikidata': 'https://www.wikidata.org/wiki/Q844240', 'display_name': 'Computer vision', 'level': 1, 'score': 0.5053635}, {'id': 'https://openalex.org/C69744172', 'wikidata': 'https://www.wikidata.org/wiki/Q860822', 'display_name': 'Image fusion', 'level': 3, 'score': 0.49636275}, {'id': 'https://openalex.org/C115961682', 'wikidata': 'https://www.wikidata.org/wiki/Q860623', 'display_name': 'Image (mathematics)', 'level': 2, 'score': 0.46287635}, {'id': 'https://openalex.org/C126780896', 'wikidata': 'https://www.wikidata.org/wiki/Q899871', 'display_name': 'Distortion (music)', 'level': 4, 'score': 0.4513905}, {'id': 'https://openalex.org/C50644808', 'wikidata': 'https://www.wikidata.org/wiki/Q192776', 'display_name': 'Artificial neural network', 'level': 2, 'score': 0.42688543}, {'id': 'https://openalex.org/C62649853', 'wikidata': 'https://www.wikidata.org/wiki/Q199687', 'display_name': 'Remote sensing', 'level': 1, 'score': 0.22090259}, {'id': 'https://openalex.org/C76155785', 'wikidata': 'https://www.wikidata.org/wiki/Q418', 'display_name': 'Telecommunications', 'level': 1, 'score': 0.07878071}, {'id': 'https://openalex.org/C205649164', 'wikidata': 'https://www.wikidata.org/wiki/Q1071', 'display_name': 'Geography', 'level': 0, 'score': 0.06777117}, {'id': 'https://openalex.org/C194257627', 'wikidata': 'https://www.wikidata.org/wiki/Q211554', 'display_name': 'Amplifier', 'level': 3, 'score': 0.0}, {'id': 'https://openalex.org/C2776257435', 'wikidata': 'https://www.wikidata.org/wiki/Q1576430', 'display_name': 'Bandwidth (computing)', 'level': 2, 'score': 0.0}], 'mesh': [], 'locations_count': 1, 'locations': [{'is_oa': False, 'landing_page_url': 'https://doi.org/10.1080/01431161.2018.1452074', 'pdf_url': None, 'source': {'id': 'https://openalex.org/S117411352', 'display_name': 'International Journal of Remote Sensing', 'issn_l': '0143-1161', 'issn': ['0143-1161', '1366-5901'], 'is_oa': False, 'is_in_doaj': False, 'is_core': True, 'host_organization': 'https://openalex.org/P4310320547', 'host_organization_name': 'Taylor & Francis', 'host_organization_lineage': ['https://openalex.org/P4310320547'], 'host_organization_lineage_names': ['Taylor & Francis'], 'type': 'journal'}, 'license': None, 'license_id': None, 'version': None, 'is_accepted': False, 'is_published': False}], 'best_oa_location': None, 'sustainable_development_goals': [], 'grants': [], 'datasets': [], 'versions': [], 'referenced_works_count': 50, 'referenced_works': ['https://openalex.org/W1247035941', 'https://openalex.org/W1507945332', 'https://openalex.org/W1511001221', 'https://openalex.org/W1654063000', 'https://openalex.org/W181107242', 'https://openalex.org/W1885185971', 'https://openalex.org/W1955857676', 'https://openalex.org/W1970836680', 'https://openalex.org/W1980110630', 'https://openalex.org/W1980444344', 'https://openalex.org/W1986629820', 'https://openalex.org/W2000323021', 'https://openalex.org/W2064366277', 'https://openalex.org/W2066812230', 'https://openalex.org/W2080159719', 'https://openalex.org/W2093602198', 'https://openalex.org/W2106891293', 'https://openalex.org/W2113338111', 'https://openalex.org/W2117146861', 'https://openalex.org/W2123046940', 'https://openalex.org/W2124743705', 'https://openalex.org/W2129953395', 'https://openalex.org/W2139529730', 'https://openalex.org/W2149720806', 'https://openalex.org/W2151794184', 'https://openalex.org/W2152254169', 'https://openalex.org/W2154789478', 'https://openalex.org/W2155893237', 'https://openalex.org/W2163605009', 'https://openalex.org/W2163677711', 'https://openalex.org/W2165329055', 'https://openalex.org/W2171108951', 'https://openalex.org/W2171211028', 'https://openalex.org/W2172185514', 'https://openalex.org/W2279059428', 'https://openalex.org/W2293167795', 'https://openalex.org/W2302265399', 'https://openalex.org/W2303172903', 'https://openalex.org/W2414425402', 'https://openalex.org/W2460041091', 'https://openalex.org/W2462592242', 'https://openalex.org/W2528170672', 'https://openalex.org/W2619662254', 'https://openalex.org/W2767166949', 'https://openalex.org/W2767224066', 'https://openalex.org/W2773069801', 'https://openalex.org/W3099843321', 'https://openalex.org/W4233918395', 'https://openalex.org/W811864384', 'https://openalex.org/W817971873'], 'related_works': ['https://openalex.org/W3007156798', 'https://openalex.org/W2565514930', 'https://openalex.org/W2375311607', 'https://openalex.org/W2361746014', 'https://openalex.org/W2158394102', 'https://openalex.org/W2143372509', 'https://openalex.org/W2124952510', 'https://openalex.org/W2022261651', 'https://openalex.org/W1930929277', 'https://openalex.org/W1502637513'], 'abstract_inverted_index': {'In': [0, 38, 116], 'this': [1, 39, 131, 140], 'paper': [2], 'we': [3, 133], 'propose': [4], 'a': [5, 44, 135], 'new': [6], 'multispectral': [7], 'image': [8], 'fusion': [9], 'architecture.': [10], 'The': [11, 95, 186], 'proposed': [12, 167, 192], 'method': [13, 42, 168, 193], 'includes': [14], 'two': [15, 19], 'steps': [16], 'related': [17], 'to': [18, 33, 50, 60, 142, 171], 'neural': [20, 47], 'networks.': [21], 'First': [22], 'the': [23, 41, 52, 56, 70, 81, 85, 99, 103, 113, 117, 120, 126, 144, 148, 154, 166, 172, 191], 'extracted': [24], 'spatial': [25, 53, 82, 100, 155, 200], 'information,': [26], 'from': [27], 'panchromatic': [28], '(Pan)': [29], 'image,': [30, 58], 'is': [31, 67, 90, 123, 159, 169], 'injected': [32], 'upsampled': [34], 'multi-spectral': [35], '(MS)': [36], 'image.': [37, 129], 'step,': [40, 119], 'employed': [43], 'deep': [45], 'convolution': [46], 'network': [48, 93, 158, 163], '(DCNN)': [49], 'estimate': [51], 'information': [54, 83, 101], 'of': [55, 74, 102], 'MS': [57, 104, 128], 'according': [59], 'multi-resolution': [61], 'analysis': [62], '(MRA)': [63], 'scheme.': [64, 115], 'This': [65, 87, 157], 'DCNN': [66, 89], 'trained': [68, 88], 'by': [69, 80], 'low-spatial': [71], 'resolution': [72], 'version': [73], 'Pan': [75], 'as': [76, 84, 108], 'an': [77, 109], 'input,': [78], 'and': [79, 106, 151, 182, 201], 'target.': [86], 'called': [91, 160], "'Fusion": [92], "(FN)'.": [94], 'FN,': [96], 'adaptively,': [97], 'estimates': [98], 'images,': [105, 150], 'operates': [107], 'injection': [110], 'gain': [111], 'in': [112, 147, 198], 'MRA': [114], 'second': [118], 'spectral': [121, 145, 202], 'compensation': [122, 162], 'performed': [124], 'on': [125, 176], 'fused': [127, 149], 'For': [130], 'purpose,': [132], 'used': [134], 'novel': [136], 'loss': [137], 'function': [138], 'for': [139], 'DCNN,': [141], 'reduce': [143], 'distortion': [146], 'simultaneously': [152], 'maintain': [153], 'information.': [156, 203], "'Spectral": [161], "(SCN)'.": [164], 'Finally,': [165], 'compared': [170], 'several': [173], 'state-of-the-art': [174], 'methods': [175], 'three': [177], 'datasets,': [178], 'using': [179], 'both': [180, 199], 'full-reference': [181], 'reduced': [183], 'reference': [184], 'criterion.': [185], 'experimental': [187], 'results': [188], 'show': [189], 'that': [190], 'can': [194], 'achieve': [195], 'competitive': [196], 'performance': [197]}, 'cited_by_api_url': 'https://api.openalex.org/works?filter=cites:W2792114281', 'counts_by_year': [{'year': 2024, 'cited_by_count': 4}, {'year': 2023, 'cited_by_count': 3}, {'year': 2022, 'cited_by_count': 5}, {'year': 2021, 'cited_by_count': 8}, {'year': 2020, 'cited_by_count': 6}, {'year': 2019, 'cited_by_count': 7}, {'year': 2018, 'cited_by_count': 2}], 'updated_date': '2024-12-09T21:00:30.651780', 'created_date': '2018-03-29'}