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| Section | Weight | Objectives |
|---|---|---|
| Principle and Application of Intelligent Video Algorithm | 3% | - Algorithm application and deployment - Common intelligent analysis algorithms |
| Intelligent Vision System Planning and Design | 15% | - Platform and service planning - System architecture and solution design - Network and storage design |
| Video Site Service Commissioning | 5% | - Link and performance commissioning - Video service activation and verification |
| Intelligent Vision System Maintenance and Troubleshooting | 7% | - Platform and service fault handling - System monitoring and routine maintenance |
| Video Interconnection Technology Standard and Application | 3% | - Mainstream interconnection protocols and standards - Interconnection solutions and implementation |
| Video Site Installation and Configuration | 18% | - Camera installation and debugging - Transmission and storage equipment deployment - Basic service configuration |
| Technical Principle and Application of Intelligent Camera | 5% | - Basic principles of intelligent cameras - Key technologies: Supercolour, T-shot, high-density capture - Application scenarios of intelligent cameras |
| Intelligent Vision System Installation and Configuration | 12% | - System parameter configuration - Platform software deployment - Access and management configuration |
| Video Site Maintenance and Troubleshooting | 5% | - Common faults diagnosis and resolution - Daily maintenance methods and procedures |
| Video Site Planning and Design | 10% | - Power supply and transmission planning - Site selection and coverage design - Equipment selection and configuration |
| Technical Principle and Application of Video Big Data | 4% | - Data storage and management technologies - Video big data processing and analysis |
| Technical Principle and Application of Video Cloud | 5% | - Cloud-based video service deployment - Video cloud architecture and features |
| Intelligent Vision System Service Commissioning | 8% | - System integration and interconnection - Core service enabling and testing |
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問題 #31
Which of the following methods can be used to fix the issue of images appearing dark in backlit scenarios?
答案：D
解題說明：
The correct answer is A because WDR is the standard method for handling scenes with strong contrast between bright background light and a darker foreground target. In a backlit scenario, the camera must balance very bright and very dark regions at the same time. If this is not handled correctly, the foreground subject appears too dark. WDR addresses exactly this problem by improving detail retention in both bright and dark parts of the scene.
This is consistent with the exposure principle emphasized in the material, which states that "T-Shot, Huawei' s patented exposure technology, enables optimal imaging of targets and vehicles at the same time" and explains that "Traditional exposure technology cannot correctly expose targets, motor vehicles, and non- motorized vehicles in one image" . That same engineering logic is what makes WDR the right correction for backlit darkness. By contrast, HLC is mainly used to suppress overly bright highlights such as headlights, not to brighten a dark foreground in a backlit scene. FoV and focal length affect framing and magnification, not dynamic-range correction. Therefore, A is the correct answer.
問題 #32
The data processing of the video big data platform includes scenarios such as real-time, full-text retrieval, and offline analysis.
答案：B
問題 #33
The video big data system can aggregate and store all kinds of video data (vehicles, faces, portraits, etc.) and perform standardized processing.
答案：B
問題 #34
Which of the following is a view library standard?
答案：C
問題 #35
The WIFI indicator of the Power Cube 500 function module shows a steady red light, indicating that the WIFI function () at this time.
答案：B
問題 #36
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