Explanation:
* CPU # Central processing unit
* GPU # Graphics processing unit
* FPGA # Field-programmable gate array
* NPU # Neural processing unit
The correct matching is based on the standard definitions of the four processor types used in intelligent vision architecture. A CPU is the central processing unit , which handles general-purpose control, logic execution, and system coordination. A GPU is the graphics processing unit , originally designed for graphics rendering but now widely used for parallel computing tasks. An FPGA is a field-programmable gate array , which can be reconfigured for specific hardware logic functions and is valuable in acceleration and low-latency processing scenarios. An NPU is a neural processing unit , specialized for AI inference and deep-learning operations.
In intelligent vision systems, these processors serve different but complementary roles. The CPU manages operating control and service orchestration. The GPU accelerates highly parallel workloads. The FPGA supports custom hardware logic and fast pipeline processing. The NPU is especially important for AI-based vision services because it is optimized for neural-network computation, target recognition, and inference efficiency. This processor division is fundamental in intelligent camera, edge, and cloud architecture, where workload specialization improves overall system performance and intelligence capability.
