How to cite this paper
Suryana, I., Chaerani, D., Muslihin, K., Irmansyah, A., Hadi, S & Prabuwono, A. (2024). Systematic literature review on optimization and exploration of retrieval methods digital image of ancient manuscript as an attempt conservation of cultural heritage.International Journal of Data and Network Science, 8(1), 453-462.
Refrences
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Bagasi, B., & Elrefaei, L. A. (2018). Arabic manuscript content based image retrieval: A comparison between SURF and BRISK local features. International Journal of Computing and Digital Systems, 7(06), 355–364.
Chen, C., Wang, X., Chen, X., Lan, R., Liu, Z., & Luo, X. (2022). Discriminative Similarity-Balanced Online Hashing for Supervised Image Retrieval. Scientific Programming, 2022. https://doi.org/10.1155/2022/2809222
Chen, Y., Zhou, X. S., & Huang, T. S. (2001). One-class SVM for learning in image retrieval. Proceedings 2001 Interna-tional Conference on Image Processing (Cat. No. 01CH37205), 1, 34–37.
Condorelli, F., & Morena, S. (2023). Integration of 3D modelling with photogrammetry applied on historical images for cultural heritage. VITRUVIO-International Journal of Architectural Technology and Sustainability, 8, 58–69.
Cotella, V. A. (2023). From 3D point clouds to HBIM: Application of Artificial Intelligence in Cultural Heritage. Automa-tion in Construction, 152, 104936.
Derviş, H. (2019). Bibliometric analysis using bibliometrix an R package. Journal of Scientometric Research, 8(3), 156–160.
Firdaniza, F., Ruchjana, B. N., Chaerani, D., & Radianti, J. (2021). Information diffusion model in twitter: A systematic literature review. Information, 13(1), 13.
Foster, G., & Kreinin, H. (2020). A review of environmental impact indicators of cultural heritage buildings: A circular economy perspective. Environmental Research Letters, 15(4), 43003.
Gao, Y., & Cao, L. (2021). Generalized optimization framework for pixel super-resolution imaging in digital holography. Optics Express, 29(18), 28805. https://doi.org/10.1364/oe.434449
Ishar, S. I., Zlatanova, S., & Roberts, J. L. (2022). 3D GAMING FOR YOUNG GENERATIONS IN HERITAGE PROTEC-TION: A REVIEW. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sci-ences, 48, 53–60.
Jayanthi, N., Indu, S., Hasija, S., & Tripathi, P. (2017). Digitization of ancient manuscripts and inscriptions-a review. Ad-vances in Computing and Data Sciences: First International Conference, ICACDS 2016, Ghaziabad, India, November 11-12, 2016, Revised Selected Papers 1, 605–612.
Kandel, S., Maddali, S., Nashed, Y. S. G., Hruszkewycz, S. O., Jacobsen, C., & Allain, M. (2021). Efficient ptychographic phase retrieval via a matrix-free Levenberg-Marquardt algorithm. Optics Express, 29(15), 23019. https://doi.org/10.1364/oe.422768
Khayyat, M. M., & Elrefaei, L. A. (2020). Manuscripts Image Retrieval Using Deep Learning Incorporating a Variety of Fusion Levels. IEEE Access, 8, 136460–136486. https://doi.org/10.1109/ACCESS.2020.3010882
Kitchenham, B. (2004). Procedures for performing systematic reviews. Keele, UK, Keele University, 33(2004), 1–26.
Lai, C.-C., & Chen, Y.-C. (2011). A user-oriented image retrieval system based on interactive genetic algorithm. IEEE Transactions on Instrumentation and Measurement, 60(10), 3318–3325.
López, F. J., Lerones, P. M., Llamas, J., Gómez-García-Bermejo, J., & Zalama, E. (2018). A review of heritage building information modeling (H-BIM). Multimodal Technologies and Interaction, 2(2), 21.
Madzík, P., Falát, L., Copuš, L., & Valeri, M. (2023). Digital transformation in tourism: bibliometric literature review based on machine learning approach. European Journal of Innovation Management, 26(7), 177–205.
Magliani, F., Sani, L., Cagnoni, S., & Prati, A. (2019). Genetic algorithms for the optimization of diffusion parameters in content-based image retrieval. Proceedings of the 13th International Conference on Distributed Smart Cameras, 1–6.
Mohammed, M. M., Badr, A., & Abdelhalim, M. B. (2015). Image classification and retrieval using optimized pulse-coupled neural network. Expert Systems with Applications, 42(11), 4927–4936.
Mohan, P. J., & Gupta, S. D. (2019). Intelligent image analysis for retrieval of leaf chlorophyll content of rice from digital images of smartphone under natural light. Photosynthetica, 57(2), 388–398. https://doi.org/10.32615/ps.2019.046
Remondino, F., & Rizzi, A. (2010). Reality-based 3D documentation of natural and cultural heritage sites—techniques, problems, and examples. Applied Geomatics, 2, 85–100.
Renita, D. B., & Christopher, C. S. (2020). Novel real time content based medical image retrieval scheme with GWO-SVM. Multimedia Tools and Applications, 79(23–24), 17227–17243.
Rodrigues, V., Eusébio, C., & Breda, Z. (2023). Enhancing sustainable development through tourism digitalisation: a sys-tematic literature review. Information Technology & Tourism, 25(1), 13–45.
Rusliana, N., Komaludin, A., & Firmansyah, M. F. (2022). A Scientometric Analysis of Urban Economic Development: R Bibliometrix Biblioshiny Application. Jurnal Ekonomi Pembangunan, 11(2), 80–94.
Sahoo, J., & Mohanty, B. (2015). Digitization of Indian manuscripts heritage: Role of the National Mission for Manu-scripts. IFLA Journal, 41(3), 237–250.
Sezavar, A., Farsi, H., & Mohamadzadeh, S. (2019). A modified grasshopper optimization algorithm combined with CNN for content based image retrieval. International Journal of Engineering, Transactions A: Basics, 32(7), 924–930. https://doi.org/10.5829/ije.2019.32.07a.04
Shukla, H. S., Kumar, N., & Tripathi, R. P. (2015). Image restoration using modified binary particle Swarm Optimization Richardson-Lucy (MBSO-RL) algorithm. Int. J. Appl. Eng. Res., 10(22), 43077–43081.
Skublewska-Paszkowska, M., Milosz, M., Powroznik, P., & Lukasik, E. (2022). 3D technologies for intangible cultural heritage preservation—literature review for selected databases. Heritage Science, 10(1), 1–24.
Syam, B., & Rao, Y. (2013). An effective similarity measure via genetic algorithm for content based image retrieval with extensive features. Int. Arab J. Inf. Technol., 10(2), 143–151.
Tonazzini, A., Salerno, E., Abdel-Salam, Z. A., Harith, M. A., Marras, L., Botto, A., Campanella, B., Legnaioli, S., Pagnot-ta, S., Poggialini, F., & others. (2019). Analytical and mathematical methods for revealing hidden details in ancient manuscripts and paintings: A review. Journal of Advanced Research, 17, 31–42.
Tsaftaris, S. A., Casadio, F., Andral, J.-L., & Katsaggelos, A. K. (2014). A novel visualization tool for art history and con-servation: Automated colorization of black and white archival photographs of works of art. Studies in Conservation, 59(3), 125–135.
Valova, I., Rachev, B., & Vassilakopoulos, M. (2006). Optimization of the algorithm for image retrieval by color features. International Conference on Computer Systems and Technologies-CompSysTech, 1–4.
Vijendran, A. S., & Deepa, C. (2014). A survey on various optimization techniques to retrieve text and images. Journal of Emerging Technologies in Web Intelligence, 6(2).
Ye, F., Meng, X., Chen, S., & Xin, J. (2021). Content-based remote sensing image retrieval based on ant colony optimiza-tion and convolutional neural networks. 2021 14th International Symposium on Computational Intelligence and Design (ISCID), 382–386.
Zhang, L., Liu, J., Yang, Y., Huang, F., Nie, F., & Zhang, D. (2020). Optimal projection guided transfer hashing for image retrieval. IEEE Transactions on Circuits and Systems for Video Technology, 30(10), 3788–3802. https://doi.org/10.1109/TCSVT.2019.2943902
Bagasi, B., & Elrefaei, L. A. (2018). Arabic manuscript content based image retrieval: A comparison between SURF and BRISK local features. International Journal of Computing and Digital Systems, 7(06), 355–364.
Chen, C., Wang, X., Chen, X., Lan, R., Liu, Z., & Luo, X. (2022). Discriminative Similarity-Balanced Online Hashing for Supervised Image Retrieval. Scientific Programming, 2022. https://doi.org/10.1155/2022/2809222
Chen, Y., Zhou, X. S., & Huang, T. S. (2001). One-class SVM for learning in image retrieval. Proceedings 2001 Interna-tional Conference on Image Processing (Cat. No. 01CH37205), 1, 34–37.
Condorelli, F., & Morena, S. (2023). Integration of 3D modelling with photogrammetry applied on historical images for cultural heritage. VITRUVIO-International Journal of Architectural Technology and Sustainability, 8, 58–69.
Cotella, V. A. (2023). From 3D point clouds to HBIM: Application of Artificial Intelligence in Cultural Heritage. Automa-tion in Construction, 152, 104936.
Derviş, H. (2019). Bibliometric analysis using bibliometrix an R package. Journal of Scientometric Research, 8(3), 156–160.
Firdaniza, F., Ruchjana, B. N., Chaerani, D., & Radianti, J. (2021). Information diffusion model in twitter: A systematic literature review. Information, 13(1), 13.
Foster, G., & Kreinin, H. (2020). A review of environmental impact indicators of cultural heritage buildings: A circular economy perspective. Environmental Research Letters, 15(4), 43003.
Gao, Y., & Cao, L. (2021). Generalized optimization framework for pixel super-resolution imaging in digital holography. Optics Express, 29(18), 28805. https://doi.org/10.1364/oe.434449
Ishar, S. I., Zlatanova, S., & Roberts, J. L. (2022). 3D GAMING FOR YOUNG GENERATIONS IN HERITAGE PROTEC-TION: A REVIEW. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sci-ences, 48, 53–60.
Jayanthi, N., Indu, S., Hasija, S., & Tripathi, P. (2017). Digitization of ancient manuscripts and inscriptions-a review. Ad-vances in Computing and Data Sciences: First International Conference, ICACDS 2016, Ghaziabad, India, November 11-12, 2016, Revised Selected Papers 1, 605–612.
Kandel, S., Maddali, S., Nashed, Y. S. G., Hruszkewycz, S. O., Jacobsen, C., & Allain, M. (2021). Efficient ptychographic phase retrieval via a matrix-free Levenberg-Marquardt algorithm. Optics Express, 29(15), 23019. https://doi.org/10.1364/oe.422768
Khayyat, M. M., & Elrefaei, L. A. (2020). Manuscripts Image Retrieval Using Deep Learning Incorporating a Variety of Fusion Levels. IEEE Access, 8, 136460–136486. https://doi.org/10.1109/ACCESS.2020.3010882
Kitchenham, B. (2004). Procedures for performing systematic reviews. Keele, UK, Keele University, 33(2004), 1–26.
Lai, C.-C., & Chen, Y.-C. (2011). A user-oriented image retrieval system based on interactive genetic algorithm. IEEE Transactions on Instrumentation and Measurement, 60(10), 3318–3325.
López, F. J., Lerones, P. M., Llamas, J., Gómez-García-Bermejo, J., & Zalama, E. (2018). A review of heritage building information modeling (H-BIM). Multimodal Technologies and Interaction, 2(2), 21.
Madzík, P., Falát, L., Copuš, L., & Valeri, M. (2023). Digital transformation in tourism: bibliometric literature review based on machine learning approach. European Journal of Innovation Management, 26(7), 177–205.
Magliani, F., Sani, L., Cagnoni, S., & Prati, A. (2019). Genetic algorithms for the optimization of diffusion parameters in content-based image retrieval. Proceedings of the 13th International Conference on Distributed Smart Cameras, 1–6.
Mohammed, M. M., Badr, A., & Abdelhalim, M. B. (2015). Image classification and retrieval using optimized pulse-coupled neural network. Expert Systems with Applications, 42(11), 4927–4936.
Mohan, P. J., & Gupta, S. D. (2019). Intelligent image analysis for retrieval of leaf chlorophyll content of rice from digital images of smartphone under natural light. Photosynthetica, 57(2), 388–398. https://doi.org/10.32615/ps.2019.046
Remondino, F., & Rizzi, A. (2010). Reality-based 3D documentation of natural and cultural heritage sites—techniques, problems, and examples. Applied Geomatics, 2, 85–100.
Renita, D. B., & Christopher, C. S. (2020). Novel real time content based medical image retrieval scheme with GWO-SVM. Multimedia Tools and Applications, 79(23–24), 17227–17243.
Rodrigues, V., Eusébio, C., & Breda, Z. (2023). Enhancing sustainable development through tourism digitalisation: a sys-tematic literature review. Information Technology & Tourism, 25(1), 13–45.
Rusliana, N., Komaludin, A., & Firmansyah, M. F. (2022). A Scientometric Analysis of Urban Economic Development: R Bibliometrix Biblioshiny Application. Jurnal Ekonomi Pembangunan, 11(2), 80–94.
Sahoo, J., & Mohanty, B. (2015). Digitization of Indian manuscripts heritage: Role of the National Mission for Manu-scripts. IFLA Journal, 41(3), 237–250.
Sezavar, A., Farsi, H., & Mohamadzadeh, S. (2019). A modified grasshopper optimization algorithm combined with CNN for content based image retrieval. International Journal of Engineering, Transactions A: Basics, 32(7), 924–930. https://doi.org/10.5829/ije.2019.32.07a.04
Shukla, H. S., Kumar, N., & Tripathi, R. P. (2015). Image restoration using modified binary particle Swarm Optimization Richardson-Lucy (MBSO-RL) algorithm. Int. J. Appl. Eng. Res., 10(22), 43077–43081.
Skublewska-Paszkowska, M., Milosz, M., Powroznik, P., & Lukasik, E. (2022). 3D technologies for intangible cultural heritage preservation—literature review for selected databases. Heritage Science, 10(1), 1–24.
Syam, B., & Rao, Y. (2013). An effective similarity measure via genetic algorithm for content based image retrieval with extensive features. Int. Arab J. Inf. Technol., 10(2), 143–151.
Tonazzini, A., Salerno, E., Abdel-Salam, Z. A., Harith, M. A., Marras, L., Botto, A., Campanella, B., Legnaioli, S., Pagnot-ta, S., Poggialini, F., & others. (2019). Analytical and mathematical methods for revealing hidden details in ancient manuscripts and paintings: A review. Journal of Advanced Research, 17, 31–42.
Tsaftaris, S. A., Casadio, F., Andral, J.-L., & Katsaggelos, A. K. (2014). A novel visualization tool for art history and con-servation: Automated colorization of black and white archival photographs of works of art. Studies in Conservation, 59(3), 125–135.
Valova, I., Rachev, B., & Vassilakopoulos, M. (2006). Optimization of the algorithm for image retrieval by color features. International Conference on Computer Systems and Technologies-CompSysTech, 1–4.
Vijendran, A. S., & Deepa, C. (2014). A survey on various optimization techniques to retrieve text and images. Journal of Emerging Technologies in Web Intelligence, 6(2).
Ye, F., Meng, X., Chen, S., & Xin, J. (2021). Content-based remote sensing image retrieval based on ant colony optimiza-tion and convolutional neural networks. 2021 14th International Symposium on Computational Intelligence and Design (ISCID), 382–386.
Zhang, L., Liu, J., Yang, Y., Huang, F., Nie, F., & Zhang, D. (2020). Optimal projection guided transfer hashing for image retrieval. IEEE Transactions on Circuits and Systems for Video Technology, 30(10), 3788–3802. https://doi.org/10.1109/TCSVT.2019.2943902