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J. Semantic Computing"],"published-print":{"date-parts":[[2024,12]]},"abstract":"<jats:p> Despite the great advances in the field of image classification, the association of ideal approaches that can bring improved results, considering different datasets, is still an open challenge. In this work, a novel approach is presented, based on a combination of compared strategies: feature extraction for early fusion; rankings based on manifold learning for late fusion; and feature augmentation applied in a long short-term memory (LSTM) algorithm. The proposed method aims to investigate the effect of feature fusion (early fusion) and ranking fusion (late fusion) in the final results of image classification. The experimental results showed that the proposed strategies improved the accuracy of results in different tested datasets (such as CIFAR10, Stanford Dogs, Linnaeus 5, Flowers 102, and Flowers 17) using a fusion of features from three convolutional neural networks (CNNs) (ResNet152, VGG16, and DPN92) and its respective generated rankings. The results indicated significant improvements and showed the potential of the approach proposed for image classification. <\/jats:p>","DOI":"10.1142\/s1793351x24440033","type":"journal-article","created":{"date-parts":[[2024,7,12]],"date-time":"2024-07-12T15:20:39Z","timestamp":1720797639000},"page":"591-612","source":"Crossref","is-referenced-by-count":1,"title":["Feature Fusion and Augmentation Based on Manifold Ranking for Image Classification"],"prefix":"10.1142","volume":"18","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-1363-5649","authenticated-orcid":false,"given":"Vanessa Helena","family":"Pereira-Ferrero","sequence":"first","affiliation":[{"name":"Department of Statistics, Applied Mathematics and Computing (DEMAC), S\u00e3o Paulo State University (UNESP), Rio Claro, 13506-900, S\u00e3o Paulo, Brazil"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3833-9072","authenticated-orcid":false,"given":"Lucas Pascotti","family":"Valem","sequence":"additional","affiliation":[{"name":"Department of Statistics, Applied Mathematics and Computing (DEMAC), S\u00e3o Paulo State University (UNESP), Rio Claro, 13506-900, S\u00e3o Paulo, Brazil"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0008-3715-8991","authenticated-orcid":false,"given":"Gustavo Rosseto","family":"Leticio","sequence":"additional","affiliation":[{"name":"Department of Statistics, Applied Mathematics and Computing (DEMAC), S\u00e3o Paulo State University (UNESP), Rio Claro, 13506-900, S\u00e3o Paulo, Brazil"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2867-4838","authenticated-orcid":false,"given":"Daniel Carlos Guimar\u00e3es","family":"Pedronette","sequence":"additional","affiliation":[{"name":"Department of Statistics, Applied Mathematics and Computing (DEMAC), S\u00e3o Paulo State University (UNESP), Rio Claro, 13506-900, S\u00e3o Paulo, Brazil"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"219","published-online":{"date-parts":[[2024,8,14]]},"reference":[{"key":"S1793351X24440033BIB001","doi-asserted-by":"publisher","DOI":"10.1109\/ISCAS.2018.8351550"},{"key":"S1793351X24440033BIB002","doi-asserted-by":"publisher","DOI":"10.1109\/AIKE55402.2022.00027"},{"key":"S1793351X24440033BIB003","doi-asserted-by":"publisher","DOI":"10.1109\/AIKE52691.2021.00027"},{"key":"S1793351X24440033BIB004","doi-asserted-by":"publisher","DOI":"10.1109\/AIKE52691.2021.00028"},{"key":"S1793351X24440033BIB005","doi-asserted-by":"publisher","DOI":"10.1109\/ACCT.2014.74"},{"issue":"23","key":"S1793351X24440033BIB006","first-page":"495","volume":"5","author":"Wu J.","year":"2017","journal-title":"Natl. 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