基于YOLOv11n的河流和湖泊空间的多目标检测
Ling Liu1, Tianyue Sun1, Xiaoying Guo2
1College of Computer and Information Engineering, Tianjin Agricultural University, Tianjin 300392, China.
Sensors (Basel, Switzerland)
|February 27, 2026
概括
本研究介绍了YOLO v11n-DDH,这是一个先进的模型,用于准确地检测河流和湖泊环境中的空间目标. 它显著提高了对污染和非法活动等问题的检测准确度.
科学领域:
- 计算机视觉 计算机视觉
- 环境监测 环境监测
- 人工智能的人工智能
背景情况:
- 河流和湖泊监测的挑战包括不同的目标尺度,不同的形状和环境干扰,如湖面反射.
- 准确的空间目标识别对于有效的环境管理和污染检测至关重要.
研究的目的:
- 提出YOLO v11n-DDH模型,以快速准确地检测河流和湖泊环境中的空间目标.
- 通过解决规模,形状和干扰等问题,增强目标识别能力.
主要方法:
- YOLO v11n-DDH 模型是基于 YOLO v11n 的,它包含了动态蛇卷积 (DySnakeConv) 来进行详细的特征提取.
- 整合可变形注意力机制 (DAttention) 以加强关键功能和减少噪音.
- 利用改进的高级选特征金字塔网络 (HSFPN) 进行有效的多级特征融合.
主要成果:
- 在自建数据集上,YOLO v11n-DDH模型的精度为88.4%,回忆率为78.9%,mAP为83.9%.
- 与原始模型相比,在精度方面有3.4%,在回忆方面有2.9%,在mAP方面有2.5%的改善.
- 具体贡献:DySnakeConv (0.6%的mAP@50增加),DAttention (0.3%的mAP@50增加),以及HSFPN (0.9%的mAP@50增加).
结论:
- YOLO v11n-DDH模型提供了一个强大的解决方案,用于识别河流和湖泊地区的各种污染物和问题.
- 这项技术为智能河流和湖泊管理系统提供了必要的技术支持.
- 可以有效识别水下废物,水质污染和非法活动.
相关概念视频
Difference from Background: Limit of Detection
8.6K
The limit of detection (LOD) is the smallest amount of analyte that can be distinguished from the background noise. The LOD value corresponds to the concentration at which the analyte signal is three times larger than the standard deviation of the blank signal. Below this value, the analyte signal cannot be differentiated from the background noise. It is calculated by dividing the calibration slope by 3 times the standard deviation of the blank signals.
The LOD indicates the presence or absence...
The LOD indicates the presence or absence...
8.6K
Design Example: Analyzing Capacity Contours for Flood Risk Assessment
342
Flood risk assessment involves careful planning and analysis to ensure the safety of communities near water retention structures. Capacity contours are a vital tool in this process, as they illustrate the potential spread of water at specific levels in a given area. In the context of building a bund across a small valley, these contours play a critical role in evaluating the safety of nearby residential areas.In this example, the bund is intended to store stormwater in the valley. The engineers...
342
Detection of Black Holes
2.6K
Although black holes were theoretically postulated in the 1920s, they remained outside the domain of observational astronomy until the 1970s.
Their closest cousins are neutron stars, which are composed almost entirely of neutrons packed against each other, making them extremely dense. A neutron star has the same mass as the Sun but its diameter is only a few kilometers. Therefore, the escape velocity from their surface is close to the speed of light.
Not until the 1960s, when the first neutron...
Their closest cousins are neutron stars, which are composed almost entirely of neutrons packed against each other, making them extremely dense. A neutron star has the same mass as the Sun but its diameter is only a few kilometers. Therefore, the escape velocity from their surface is close to the speed of light.
Not until the 1960s, when the first neutron...
2.6K
Classification of Systems-II
540
Continuous-time systems have continuous input and output signals, with time measured continuously. These systems are generally defined by differential or algebraic equations. For instance, in an RC circuit, the relationship between input and output voltage is expressed through a differential equation derived from Ohm's law and the capacitor relation,
540
Testing Water Quality
423
When the quality of water for concrete preparation is uncertain, its impact on the setting time of cement and compressive strength of mortar is assessed by comparison with de-ionized or distilled water benchmarks. American Society for Testing and Materials (ASTM) C1602 requires the setting times to be within 90 minutes of the control, British Standard (BS) 3146:1980 allows a 30-minute variance in the initial setting, while British Standards European Norm (BS EN) 1008 specifies initial setting...
423
Uniform Depth Channel Flow: Problem Solving
560
To calculate the flow rate for a trapezoidal channel, first, identify the bottom width, side slope, and flow depth of the channel. The cross-sectional area (A) corresponding to the depth of flow (y), channel bottom width (B), and side slope (θ) is determined by:Next, calculate the wetted perimeter, which includes the bottom width and the sloped side lengths in contact with the water. Using the values of the cross-sectional area and the wetted perimeter, determine the hydraulic radius by...
560
