Deep learning is an important research field of machine learning. In recent years, many breakthroughs have been made in the field of target detection, which has been applied to specific target detection tasks. This paper first introduces the representative traditional detection methods and discusses ...
2) 使用标注了object信息的detection的数据库,transfer什么是一个object的知识,这其中既有基于object proposal的方法,也有基于deep learning的一些尝试。3) 以去年VOT比赛冠军MDCNN为代表,使用标注了association的视频作为训练数据,transfer同一物体在视频中不同帧的表示到tracking中。个人觉得MDCNN做出了一个很好的尝试,SOT...
In addition, the self-produced data set of field construction vehicles was used to detect Yolov3 and test the detection accuracy. The results showed that the detection accuracy was above 0.9. Yolov3 can be well used for vehicle detection. Finally, the detection methods based on deep learning ...
Small target with different size and insignificant feature are easily overwhelmed by the background leading to inaccurate detection of target. Deep learning is based on data-driven learning of target feature, which has been quite effective in the field of computer vision in recent years. Thanks to...
In order to solve the problem that some semantic information in sonar images is lost and model detection performance is degraded due to the complex imaging environment, we proposed a more effective and robust target detection framework based on deep learning, which can make full use of the ...
Traditional radar target detection method performs not good enough in the complex scene which consist of multi sidelobe jamming, non-homogeneous and non-stability clutter with strict probability of detection. The performance need to be further
To improve the accuracy and anti-noise performance of underwater target image edge detection, an underwater target edge detection method based on ant colony optimization and reinforcement learning is proposed in this paper. First, the reinforcement learning concept is integrated into artificial ants’ ...
Particleboard surface defect detection technology is of great significance to the automation of particleboard detection, but the current detection technology has disadvantages such as low accuracy and poor real-time performance. Therefore, this paper pro
At present, YOLOv4 is the most popular target detection method based on deep learning with high speed and accuracy. However, the YOLOv4 experiment was usually carried out in the MS COCO dataset and is not fully applicable to UAV imagery. Due to the problems of complex background, small targ...
Deep learning-driven underwater polarimetric target detection based on the dispersion of polarization characteristics Underwater target detectionPolarization dispersionDeep learningMaterial recognitionThe dispersion values of AOP and DOLP of dataset are extracted by our neural ... G Wang,J Gao,Y Xiang,....