Guest Editor(s)
Assoc. Prof. Nicoletta Saulig
Email: nsaulig@unipu.hr
Affiliation: Faculty of Engineering, Juraj Dobrila University of Pula, Pula, Croatia
Homepage:
Research Interests: multimodal image and signal analysis, time–frequency analysis of nonstationary signals, statistical signal and image processing, complexity estimation and information-theoretic analysis, multiscale modeling of signals and images (wavelet-based approaches), texture analysis and structural complexity quantification
Assoc. Prof. Željka Tomasović
Email: ztomasovi22@unizd.hr
Affiliation: Department of Information Sciences and Technologies, University of Zadar, Zadar, Croatia
Homepage:
Research Interests: nanoelectronics, optoelectronics, time-frequency analysis, statistical signal analysis, digital image processing and analysis, compute vision, digital humanities
Prof. Marijana Tomić
Email: mtomic@unizd.hr
Affiliation: Department of Information Sciences and Technologies, University of Zadar, Zadar, Croatia
Homepage:
Research Interests: bibliographic organization of information, cataloguing, digitization, preservation, and communication of old and rare books and manuscripts, digital cultural heritage, digital humanities, croatian glagolitic manuscripts and early printed books, croatian glagolitism
Summary
This Special Issue addresses the growing role of artificial intelligence, multimodal image analysis, and data fusion, as well as computational modeling, in the study and management of complex visual and material data. Its relevance lies in the convergence of computer science, multimedia processing, big data management, software engineering, and data-driven modeling, together with theoretical approaches for analyzing complex visual and material systems. Such data increasingly originate from diverse sources and modalities, including cultural heritage objects, medical images, industrial imaging, scientific imaging data, artworks, and other complex visual or multimodal resources. Many of these datasets represent objects or structures whose visual, spatial, structural, and compositional properties require advanced sensing, multimodal integration, interpretation, theoretical models, and computational analysis.
The aim of this Special Issue is to bring together original research on AI-based image analysis, multimodal data fusion, scalable data infrastructures, and computational methods for the representation, interpretation, and long-term management of complex visual and material data. In line with the journal's scope, the issue especially welcomes contributions in artificial intelligence, big data analytics, multimedia, software systems, high-performance computing, and modeling approaches that support the analysis of heterogeneous visual and material datasets across multiple modalities.
Suggested Special Issue Topics (not limited to):
· Multimodal sensing
· Multimodal data fusion for heterogeneous imaging datasets
· Deep learning and foundation models for image interpretation
· Explainable AI for complex visual and material data
· 3D reconstruction and geometric modeling from multimodal image data
· Automated defect, anomaly, and pattern detection in complex surfaces and layered structures
· Compression, storage, and transmission of large multimodal datasets
· Semantic integration of image, sensor, and textual data
· Intelligent indexing, retrieval, and recommendation in large image collections
· Sensor calibration, registration, and uncertainty estimation in multimodal imaging
· Super-resolution, denoising, and restoration in scientific and technical imaging
· Graph-based learning for multimodal data organization and analysis
· Data fusion for industrial, biomedical, and heritage imaging
· Image-based monitoring and predictive analysis of physical systems
· Large-scale visual analytics for scientific and engineering collections
· Multimodal Document Layout Segmentation and Structural Analysis
· Named Entity Recognition and Semantic Enrichment Using AI
Keywords
artificial intelligence, multimodal data fusion, image analysis, computational modeling
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