Real-time target detection and location has important values in video surveillance. Aimed at the low accuracy of existing real-time object detection algorithms, this paper proposes a multi-scale real-time target detection algorithm based on residual convolution neural network. Firstly, the residual ...
Humans glance at an image and instantly know what objects are in the image, where they are, and how they interact. The human visual system is fast and accurate, allowing us to perform complex tasks like driving with little conscious thought. Fast, accurate algorithms for object detection would...
[2] L. Bourdev and J. Malik. Poselets: Body part detectors trained using 3d human pose annotations. In International Conference on Computer Vision (ICCV), 2009. 8 [3] H. Cai, Q. Wu, T. Corradi, and P. Hall. The crossdepiction problem: Computer vision algorithms for recognising object...
where they are, and how they interact. The human visual system is fast and accurate, allowing us to perform complex tasks like driving with little conscious thought. Fast, accurate algorithms for object detection would allow computers to drive cars without specialized sensors, enable assistive device...
However, due to the small size and high density of objects from the aerial perspective, most existing algorithms are difficult to accurately process and extract informative features from the traffic images collected by UAVs. To address the challenges, this paper proposes a new real-time small ...
Overall, camera-based object detection algorithms are easily affected by changes in light intensity. As a result, they are unstable when working in real environments. Besides, their detection accuracy rate for occluded targets is not high enough. The accuracy rates of LiDAR-based object detection ...
Fast, accurate, algorithms for object detection would allow computers to drive cars in any weather without specialized sensors, enable assistive devices to convey real-time scene information to human users, and unlock the potential for general purpose, responsive robotic systems. ...
Object detection, as a major task of computer vision, inevitably needs to adapt to edge equipment when moving from laboratory to application, which will face the limited resources. The measurement standards of the previous classical detection algorithms are focus on the detection accuracy, verified on...
Focal loss is combined with the CIOU_Loss algorithm to introduce the MYOLO-lite loss function of the object detection algorithm. 3.4.1. CIOU Loss Function In YOLO V4, the use of CIOU_Loss algorithms for the calculation of the object detection loss function is proposed, and the CIOU formula...
The task of UAV-based maritime rescue object detection faces two significant challenges: accuracy and real-time performance. The YOLO series models, known for their streamlined and fast performance, offer promising solutions for this task. However, existing YOLO-based UAV maritime rescue object detecti...