Editorial: Recent trends in multimedia forensics and visual content verification
Abstract
Huge amounts of multimedia content are in fact generated every day, pervading the web and popular sharing platforms such as social networks. Such data carry embedded traces due to the whole creation and sharing cycle, which can be recovered and exploited to assess the authenticity of a specific asset. This includes identifying the provenance of media data, the generation device or crafting method, as well as potential manipulation of the multimedia signal. Also, the massive introduction of artificial intelligence and of modern performing devices, together with new paradigms for content sharing and fruition, have determined the need to research novel methodologies that can globally take into account all these important changes. This Research Topic gathers cutting-edge techniques for the forensic analysis and verification of media data, including solutions at the edge of signal processing, machine/deep learning, and multimedia analysis.Research approaches to multimedia forensics have rapidly evolved in the last years, as a consequence of both technological advancements in media creation and distribution, and methodological advancements in signal processing and learning. One evident aspect is the disruptive diffusion of deep learning models for addressing tasks related to audio-visual data. As a consequence of the impressive performance boost they brought in different areas, deep architectures nowadays dominate in multimedia forensics research as well. Then, forensic…
Read the paper
Related studies
- Learning from First-Generation Qualitative Approaches in the IS Discipline: An Evolutionary View and Some Implications for Authors and Evaluators (PART 1/2)
- Commentary on the clinical and preclinical dosage limits of interstitially administered magnetic fluids for therapeutic hyperthermia based on current practice and efficacy models
- Prosthesis: New Technological Opportunities and Innovative Biomedical Devices
- The history and future of neural modeling for cochlear implants
- Ryanodine receptors: waking up from refractoriness
- Novel Transgenic Rabbit Model Sheds Light on the Puzzling Role of Matrix Metalloproteinase-12 in Atherosclerosis
Go deeper in Evidence Hub
Evidence Hub adds a study data sheet (design, sample size, evidence level, key numbers), an AI summary and a chat grounded in the paper's text.