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English Information

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Authors
# Name
1 Rodrigo César Arboleda(rodrigo_arboleda@hotmail.com.br)
2 Caetano Traina Jr.(caetano@icmc.usp.br)
3 Agma Traina(agma@icmc.usp.br)

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Reference
# Reference
1 Abdel-Hamid, L. (2024). Multiresolution analysis for covid-19 diagnosis from chest ct images: wavelet vs. contourlet transforms. Multimedia Tools and Applications, 83(1):2749–2771.
2 Berchtold, S., Keim, D. A., and Kriegel, H.-P. (1996). The x-tree: An index structure for high-dimensional data. In Very large data-bases, pages 28–39.
3 Cazzolato, M. T., Rodrigues, L. S., Ribeiro, M. X., Gutierrez, M. A., Traina Jr, C., and Traina, A. J. M. (2022). Sketch+ for visual and correlation-based exploratory data analysis: A case study with COVID-19 databases. JIDM – Journal of Information and Data Management, 13(2):308.
4 Cazzolato, M. T., Rodrigues, L. S., Scabora, L. d. C., Zabot, G. F., Vasconcelos, G. Q., Chino, D. Y. T., Jorge, A. E. S., Cordeiro, R. L. F., Traina Jr, C., and Traina, A. J. M. (2019). A DBMS-based framework for content-based retrieval and analysis of skin ulcer images in medical practice. In Proceedings of SBBD 2019, pages 109–120, Fortaleza, CE, Brazil. SBC.
5 Chen, L., Gao, Y., Song, X., Li, Z., Zhu, Y., Miao, X., and Jensen, C. S. (2023). Indexing metric spaces for exact similarity search. ACM Comput. Surv., 55(6):39.
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8 Elharrouss, O., Akbari, Y., Almadeed, N., and Al-Maadeed, S. (2024). Backbones- review: Feature extractor networks for deep learning and deep reinforcement learning approaches in computer vision. Computer Science Review, 53:22.
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12 Khosla, A., Jayadevaprakash, N., Yao, B., and Fei-Fei, L. (2011). Novel dataset for fine- grained image categorization. In IEEE Conference on Computer Vision and Pattern Recognition First Workshop on Fine-Grained Visual Categorization, Colorado Springs, CO.
13 Marques, P. M. d. A. and Rangayyan, R. M. (2013). Content-based Retrieval of Med- ical Images: Landmarking, Indexing, and Relevance Feedback. Synthesis Lectures on Biomedical Engineering. Morgan & Claypool Publishers, San Rafael, California, USA.
14 Mulcahy, C. (1997). Image compression using the haar wavelet transform. Spelman Science and Mathematics Journal, 1(1):22–31.
15 Santana, D. R. and Ribeiro, L. A. (2023). Approximate similarity joins over dense vector embeddings. In Proceedings of SBBD 2023, pages 51–62. SBC.
16 Saouabe, A., Tkatek, S., Oualla, H., and Mourtaji, I. (2024). Image indexing approaches for enhanced content-based image retrieval: An overview.
17 Sharma, S., Gupta, V., and Juneja, M. (2019). A survey of image data indexing techniques. Artificial Intelligence Review, 52(2):1189–1266.
18 Traina Jr, C., Traina, A., Seeger, B., and Faloutsos, C. (2000). Slim-trees: High perfor- mance metric trees minimizing overlap between nodes. In International Conference on Extending Database Technology, pages 51–65. Springer.
19 Vadivel, A., Majumdar, A., and Sural, S. (2003). Performance comparison of distance metrics in content-based image retrieval applications. In International Conference on Information Technology (CIT), Bhubaneswar, India, pages 159–164.
20 Yianilos, P. N. (1993). Data structures and algorithms for nearest neighbor search in general metric spaces. In Fourth Annual ACM/SIGACT-SIAM Symposium on Discrete Algorithms (SODA), pages 311–321, Austin, TX.
21 Zaki, M. J. and Meira, W. (2020). Data Mining and Machine Learning: Fundamental Concepts and Algorithms (https://dataminingbook.info/book_html/). Cambridge Uni- versity Press, 2nd edition.
22 Zezula, P., Amato, G., Dohnal, V., and Batko, M. (2006). Similarity Search: The Metric Space Approach. Advances in Database Systems. Springer New York, New York, NY, USA.