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| Section | Objectives |
|---|---|
| Computer Vision Fundamentals | - Image representation and processing basics
|
| Huawei AI Platform and Deployment | - Edge and cloud deployment
|
| Deep Learning for Vision | - Model training and evaluation
|
| Intelligent Vision Applications | - Video analysis
|
>> H12-521_V1.0 Answers Real Questions <<
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NEW QUESTION # 27
For Huawei HoloSens IVS1800 multi-machine deployment network, what is the largest access scale of an iClent client camera?
Answer: A
NEW QUESTION # 28
There are many ways to configure the camera's IP address, including (). (Multiple choice)
Answer: A,B,C,D
NEW QUESTION # 29
Processors are important to the Intelligent Vision system, and different processors have different functions.
Link the following processor types to the corresponding description.
Answer:
Explanation:
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.
NEW QUESTION # 30
Which of the following are included in the routine check of the CSP?
Answer: A,B,C,D
Explanation:
The Cloud Service Platform (CSP) is the underlying infrastructure that manages containers, resources, and services for the intelligent vision platform. Routine maintenance and health checks are essential to ensure the continuous availability of video surveillance services. A comprehensive routine check of the CSP encompasses multiple layers of the system architecture.
First, the License status must be verified to ensure that all intelligent functions and channel capacities remain authorized and active. Second, monitoring CPU and memory usage is critical to identify potential resource bottlenecks that could lead to service instability or video stuttering. Third, for systems deployed in high- availability environments, the Cluster running status (including two-node cluster heartbeat and synchronization) must be checked to ensure failover capabilities are intact. Finally, since the platform utilizes a microservice architecture, checking the CSP and container running status is mandatory to verify that all functional modules (like the VCNAPI or BMU) are active and isolated as intended. By performing these checks regularly, administrators can proactively address issues before they trigger critical system alarms or data loss.
NEW QUESTION # 31
Machine vision uses cameras and computers instead of human eyes to identify, track, and measure targets. Computers are used for further graphic processing to finally obtain the data and results we need.
Answer: B
NEW QUESTION # 32
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