Understanding how humans interact with objects in complex visual scenes is fundamental to human-centric artificial intelligence. Yet, current Human-Object Interaction (HOI) detection frameworks often falter when faced with visual occlusions, vague interaction semantics, and scenarios that extend beyond predefined categ...
A. Abdusalomov, Utkir Xudoynazarov, U. Ruziev et al.· Scientific Reports· 0 citations
: Wireless sensor networks (WSNs) and Internet of Things (IoT) systems require lightweight cryptographic primitives that provide strong security under strict constraints on area, latency, and timing predictability. Ascon, selected by National Institute of Standards and Technology (NIST) as the standard for lightweight...
Kuldashbay Avazov, J. Sevinov, Komil Tashev et al.· Computers, Materials & C...· 0 citations
A fusion-based artificial intelligence framework that integrates Quantization-Aware Training (QAT)-optimized PointNet++ models with machine-learning regression to predict a short-term dendrometer-derived stem-diameter response expressed in biomass-equivalent units is proposed.
Furkat Bolikulov, K. Zohirov, Gayrat Mannonov et al.· Italian National Conference...· 0 citations
NEO-STREAM, a compliance-aware transformer-based framework for real-time fraud detection that employs micro-episode tokenization to capture short-term behavioral patterns without relying on long-term user histories, indicates that compliance-aware AI architectures can effectively bridge the gap between predictive perfo...
A. Abdusalomov, Alpamis Kutlimuratov, Cüneyt Şamil Oğurlu· 0 citations
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