Optimizing multimodal scene recognition through relevant feature selection approach for scene classification
Scene classification plays a vital role in various computer vision applications, but building deep learning models from scratch is a very time-intensive process. Transfer learning is an excellent classification method using the predefined model. In our proposed work, we introduce a novel method of m...
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| Format: | Article |
| Language: | English |
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Elsevier
2025-06-01
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| Series: | MethodsX |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S2215016125000731 |
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| author | Sumathi K Pramod Kumar S H R Mahadevaswamy Ujwala B S |
| author_facet | Sumathi K Pramod Kumar S H R Mahadevaswamy Ujwala B S |
| author_sort | Sumathi K |
| collection | DOAJ |
| description | Scene classification plays a vital role in various computer vision applications, but building deep learning models from scratch is a very time-intensive process. Transfer learning is an excellent classification method using the predefined model. In our proposed work, we introduce a novel method of multimodal feature extraction and a feature selection technique to improve the efficiency of transfer learning in scene classification. We leverage widely used convolutional neural networks (CNN) for feature extraction, followed by relevant feature selection techniques to enhance the performance of the model and increase computational efficiency. In this work, we have executed the proposed method on the Scene dataset of 6 classes and the AID dataset. Experimental results indicate that the MIFS-based approach reduces computational overhead and achieves competitive or superior classification accuracy. The proposed methodology offers a scalable and effective solution for scene classification tasks, with potential applications in real-time recognition and automated systems. |
| format | Article |
| id | doaj-art-ce0cf90f1b5d461589efe6a8b85a5e52 |
| institution | OA Journals |
| issn | 2215-0161 |
| language | English |
| publishDate | 2025-06-01 |
| publisher | Elsevier |
| record_format | Article |
| series | MethodsX |
| spelling | doaj-art-ce0cf90f1b5d461589efe6a8b85a5e522025-08-20T02:35:30ZengElsevierMethodsX2215-01612025-06-011410322610.1016/j.mex.2025.103226Optimizing multimodal scene recognition through relevant feature selection approach for scene classificationSumathi K0Pramod Kumar S1H R Mahadevaswamy2Ujwala B S3JNN College of Engineering, Shimoga, Karnataka, India; Corresponding author.JNN College of Engineering, Shimoga, Karnataka, IndiaJSS Mahavidyapeetha, Visvesvaraya Technological University, Mysore, Karnataka, IndiaJNN College of Engineering, Shimoga, Karnataka, IndiaScene classification plays a vital role in various computer vision applications, but building deep learning models from scratch is a very time-intensive process. Transfer learning is an excellent classification method using the predefined model. In our proposed work, we introduce a novel method of multimodal feature extraction and a feature selection technique to improve the efficiency of transfer learning in scene classification. We leverage widely used convolutional neural networks (CNN) for feature extraction, followed by relevant feature selection techniques to enhance the performance of the model and increase computational efficiency. In this work, we have executed the proposed method on the Scene dataset of 6 classes and the AID dataset. Experimental results indicate that the MIFS-based approach reduces computational overhead and achieves competitive or superior classification accuracy. The proposed methodology offers a scalable and effective solution for scene classification tasks, with potential applications in real-time recognition and automated systems.http://www.sciencedirect.com/science/article/pii/S2215016125000731Multimodal Feature extraction and Relevant Feature selection using Filter and Embedded approach |
| spellingShingle | Sumathi K Pramod Kumar S H R Mahadevaswamy Ujwala B S Optimizing multimodal scene recognition through relevant feature selection approach for scene classification MethodsX Multimodal Feature extraction and Relevant Feature selection using Filter and Embedded approach |
| title | Optimizing multimodal scene recognition through relevant feature selection approach for scene classification |
| title_full | Optimizing multimodal scene recognition through relevant feature selection approach for scene classification |
| title_fullStr | Optimizing multimodal scene recognition through relevant feature selection approach for scene classification |
| title_full_unstemmed | Optimizing multimodal scene recognition through relevant feature selection approach for scene classification |
| title_short | Optimizing multimodal scene recognition through relevant feature selection approach for scene classification |
| title_sort | optimizing multimodal scene recognition through relevant feature selection approach for scene classification |
| topic | Multimodal Feature extraction and Relevant Feature selection using Filter and Embedded approach |
| url | http://www.sciencedirect.com/science/article/pii/S2215016125000731 |
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