FADRW: A Feature-Aware Modulated and Dynamically Reweighted Loss for Few-Shot Linguistic Steganalysis
arXiv 2606.07655•41fc4fb363818e9b8c9579ea382989cf5aa9a3cd6d98380900da72062626331f
EEGIMUSHAPWiener filterantenna arraysattitude determinationbeamforming','modulation recognition','mixture-of-experts','I/Qclass imbalancedirection-of-arrival (DoA)electromagnetic modelingexplainabilityfeature modulationfew-shot learninggraph signal processingimpulsive noiselinguistic steganographyloss functionmedical AIseizure predictionsignal processingsocial media securitysparse adaptive filtersteganalysistunnel propagationwireline equalization
Paper metadata
- arXiv ID
- 2606.07655
- Version
- Not specified by this published record
- Category
- Electrical Engineering and Systems Science — Signal Processing (eess.SP)
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Evidence and limitations
- Source ID
- arxiv_eess_sp
- Record identifier
- 41fc4fb363818e9b8c9579ea382989cf5aa9a3cd6d98380900da72062626331f
- Enrichment time
- 2026-06-09T08:51:43Z
- AI-assisted enrichment
- Yes
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