RSO-YOLO:在自动驾驶场景中实时检测小物体和封闭物体的实时探测器
Quanxiang Wang1, Zhaofa Zhou1, Zhili Zhang1
1School of Missile Engineering, Rocket Force University of Engineering, Xi'an 710025, China.
Sensors (Basel, Switzerland)
|November 13, 2025
概括
RSO-YOLO通过改进小物体和封闭物体的识别来增强自动驾驶的物体检测. 这种先进的模型在降低参数和计算复杂度的情况下实现了更高的准确性.
科学领域:
- 计算机视觉 计算机视觉
- 自主系统 自主系统
- 机器学习 机器学习
背景情况:
- 检测小物体和封闭物体是自动驾驶的关键挑战.
- 现有的模型难以应对现实世界驾驶场景的复杂性和变化.
研究的目的:
- 开发一个增强的物体检测模型,RSO-YOLO,以提高自动驾驶的性能.
- 专门解决检测小物体和封闭物体的局限性.
主要方法:
- 基于YOLOv12,RSO-YOLO结合了双向特征金字塔网络 (BiFPN) 和空间到深度卷积 (SPD-Conv).
- 增加了P2特征层的检测头和特征增强和补偿模块 (FECM),以改善小物体和封闭物体的检测.
- 一个轻量级的全球跨维坐标检测头 (GCCHead) 被开发出来,以平衡效率和性能.
主要成果:
- 与YOLOv12.2相比,RSO-YOLO实现了显著的mAP@0.5改进:SODA10M上的8.0%,BDD100K上的10.7%,FLIR ADAS上的7.2%,与YOLOv12.2相比,RSO-YOLO实现了显著的mAP@0.5改进:SODA10M上的8.0%,BDD100K上的10.7%,FLIR ADAS上的7.2%.
- 该模型将参数减少了15.4%,计算复杂性减少了20%.
- 证明了在遮蔽下更高的检测准确性和稳定性.
结论:
- RSO-YOLO为自动驾驶系统提供了卓越的物体检测功能.
- 该模型通过提高准确度,同时降低计算需求,提供了一个实际的解决方案.
- RSO-YOLO显示了现实世界自动驾驶应用的巨大潜力.
相关概念视频
Detection of Black Holes
2.5K
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...
2.5K
Difference from Background: Limit of Detection
8.0K
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...
8.0K
Design Example: Measuring Distance Between Two Points with Obstructions
381
When measuring distances in areas with physical obstructions, such as a lake in a field, surveyors must employ techniques to calculate accurate lengths without direct line measurements. One effective method is the offset technique, which allows for precise distance estimation over inaccessible stretches.In this scenario, a surveyor must measure a side of an area that crosses a lake. Since the measuring tape cannot span the lake, the surveyor begins by establishing a baseline that aligns with...
381
Depth Perception and Spatial Vision
1.8K
Depth perception is the ability to perceive objects three-dimensionally. It relies on two types of cues: binocular and monocular. Binocular cues depend on the combination of images from both eyes and how the eyes work together. Since the eyes are in slightly different positions, each eye captures a slightly different image. This disparity between images, known as binocular disparity, helps the brain interpret depth. When the brain compares these images, it determines the distance to an object.
1.8K
Relative Motion Analysis using Rotating Axes-Problem Solving
689
Consider a crane whose telescopic boom rotates with an angular velocity of 0.04 rad/s and angular acceleration of 0.02 rad/s2. Along with the rotation, the boom also extends linearly with a uniform speed of 5 m/s. The extension of the boom is measured at point D, which is measured with respect to the fixed point C on the other end of the boom. For the given instant, the distance between points C and D is 60 meters.
Here, in order to determine the magnitude of velocity and acceleration for point...
Here, in order to determine the magnitude of velocity and acceleration for point...
689
Collisions in Multiple Dimensions: Problem Solving
5.2K
In multiple dimensions, the conservation of momentum applies in each direction independently. Hence, to solve collisions in multiple dimensions, we should write down the momentum conservation in each direction separately. To help understand collisions in multiple dimensions, consider an example.
A small car of mass 1,200 kg traveling east at 60 km/h collides at an intersection with a truck of mass 3,000 kg traveling due north at 40 km/h. The two vehicles are locked together. What is the...
A small car of mass 1,200 kg traveling east at 60 km/h collides at an intersection with a truck of mass 3,000 kg traveling due north at 40 km/h. The two vehicles are locked together. What is the...
5.2K


