Enhancing Content-Based Image Retrieval with a Stacked Ensemble of Deep Learning Models

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dc.contributor.authorZeain, Abdulrahman
dc.contributor.authorIbrahim, Abdullahi Abdu
dc.date.accessioned2025-02-28T11:57:25Z
dc.date.available2025-02-28T11:57:25Z
dc.date.issued2024
dc.departmentFakülteler, Mühendislik ve Doğa Bilimleri Fakültesi, Bilgisayar Mühendisliği Bölümü
dc.description.abstractOur research paper delves into an innovative exploration of content-based image retrieval (CBIR), harnessing the capabilities of deep learning models to transform the way images are searched and accessed in extensive databases. The primary goal of our study is to create an ensemble stacking model that synergizes the strengths of various deep learning architectures, thereby boosting the accuracy and efficiency of image retrieval processes. We utilize the Corel Images dataset, rich in diverse visual themes, to test and validate our model's efficacy. Our research methodology encompasses four key stages: data preprocessing, model training with DenseNet, MobileNet, and Inception-ResNet, followed by an in-depth evaluation of the model. The approach demonstrates the effectiveness of our ensemble model as it achieves a high accurate rate of 97 % exceeds the benchmarks set by the individual models in our compare and differential analyses. Moreover, the manuscript investigates the model's technical detail, such as the feature extraction, runtime with different images, and scalability to more massive datasets. The eulogy for the model's performance in the performance evaluation section encapsulates the functional performance and the practicality of CBIR efficacy.
dc.identifier.citationZeain, A., & Ibrahim, A. A. (2024, December). Enhancing Content-Based Image Retrieval with a Stacked Ensemble of Deep Learning Models. In 2024 8th International Symposium on Innovative Approaches in Smart Technologies (ISAS) (pp. 1-11). IEEE.
dc.identifier.doi10.1109/ISAS64331.2024.10845555
dc.identifier.isbn9798331540104
dc.identifier.scopus2-s2.0-85218035471
dc.identifier.urihttps://hdl.handle.net/20.500.12939/5720
dc.indekslendigikaynakScopus
dc.institutionauthorZeain, Abdulrahman
dc.institutionauthorIbrahim, Abdullahi Abdu
dc.institutionauthorid0000-0002-5599-348X
dc.language.isoen
dc.publisherInstitute of Electrical and Electronics Engineers Inc.
dc.relation.ispartof8th International Symposium on Innovative Approaches in Smart Technologies, ISAS 2024 - Proceedings
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Öğrenci
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.subjectand inception-resnet
dc.subjectcontent-based image retrieval
dc.subjectdeep learning
dc.subjectdensenet
dc.subjectmobilenet
dc.subjectpre-trained models
dc.titleEnhancing Content-Based Image Retrieval with a Stacked Ensemble of Deep Learning Models
dc.typeConference Object

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