COMPARATIVE STUDY OF FEATURE-LEVEL AND DECISION-LEVEL FUSION STRATEGIES IN NEURAL NETWORK MODELS FOR MULTIMODAL PSYCHODIAGNOSTICS

Abrarov, Rinat

Techscience.uz - техника фанлари долзарб масалалри · 2025-yil

Annotatsiya

This paper examines the effectiveness of feature-level and decision-level fusion strategies in neural network models for multimodal psychodiagnostics. Findings indicate that feature-level fusion enhances information extraction, while decision-level fusion improves diagnostic accuracy. A hybrid approach ensures greater reliability and expands applications in clinical practice

Maqola ma’lumotlari
MualliflarAbrarov, Rinat
JurnalTechscience.uz - техника фанлари долзарб масалалри
Nashr sanasi2025-10-11
Jild3
Son8
Betlar14-27
TilIngliz
DOI10.47390/ts-v3i8y2025no3

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