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The proliferation of software-defined vehicles, centralized compute architectures, connected services, and over-the-air software updates is fundamentally transforming automotive cybersecurity from a product development activity to a continuous operational discipline. As connected vehicle ecosystems expand, OEMs require capabilities that extend beyo...

This study examines the emerging landscape of neuromorphic computing and its role in enabling low-power, real-time, brain-inspired intelligence across edge and autonomous systems. It reviews advancements in spiking neural networks, memristor-based computing in memory, event-driven vision sensors, and hybrid neuromorphic and conventional architectur...

Quantum sensing is transitioning from laboratory research to industrial deployment, driven by the need for ultra-precise, reliable measurement in high-impact sectors such as healthcare, defense, and advanced manufacturing. This shift reflects a broader move from controlled, research-grade environments toward scalable, field-ready systems that meet ...

Multimodal sensor fusion is an advanced perception technology that combines data from multiple sensors, including cameras, LiDAR, radar, ultrasonic sensors, thermal cameras, and inertial measurement units (IMUs), to give robots and autonomous systems a more accurate, reliable, and comprehensive understanding of their environment. It overcomes the l...

Hybrid vision systems (HVS) are positioned to substantially impact perception-driven applications across a diverse array of sectors, including robotics, manufacturing, logistics, mobility, surveillance, and agriculture. By intricately combining the geographical precision of LiDAR with the semantic intelligence of advanced imaging systems, these inn...