Practical Approach for Processing and Fusion of Multimodal Data for Reconnaissance
Refiz Duro, Axel Weißenfeld, Christoph Singewald, Medina Andreşel, Dražen Ignjatović, Veronika Siska · 2024
Processing and fusion of multimodal reconnaissance data is critical in the context of intelligence gathering and decision support. We examine the implementation of a suitable architecture and demonstrate the processing and data fusion by exploiting AI-based transcription, translation and Large Language Model information extraction components using audio and text data. We also highlight the potential benefits and challenges of integrating them into intelligence workflows. A possible categorisation of data processing and fusion components according to their practical role is provided.